update

.history/IE-SemParse_20230707234104.py

@@ -0,0 +1,162 @@
+# coding=utf-8
+
+
+# Lint as: python3
+"""IndicXNLI: The Cross-Lingual NLI Corpus for Indic Languages."""
+
+
+import os
+import json
+
+import pandas as pd
+
+import datasets
+
+from datasets import DownloadManager
+
+
+_CITATION = """\
+@misc{aggarwal2023evaluating,
+      title={Evaluating Inter-Bilingual Semantic Parsing for Indian Languages}, 
+      author={Divyanshu Aggarwal and Vivek Gupta and Anoop Kunchukuttan},
+      year={2023},
+      eprint={2304.13005},
+      archivePrefix={arXiv},
+      primaryClass={cs.CL}
+}
+"""
+
+_DESCRIPTION = """\
+    IE-SemParse is an Inter-bilingual Seq2seq Semantic parsing dataset for 11 distinct Indian languages
+"""
+
+_LANGUAGES = (
+    'hi',
+    'bn',
+    'mr',
+    'as',
+    'ta',
+    'te',
+    'or',
+    'ml',
+    'pa',
+    'gu',
+    'kn'
+)
+
+
+_DATASETS = (
+    'itop',
+    'indic-atis',
+    'indic-TOP'
+)
+
+
+_URL = "https://huggingface.co/datasets/Divyanshu/IE-SemParse/resolve/main/"
+
+
+class IESemParseConfig(datasets.BuilderConfig):
+    """BuilderConfig for IE-SemParse."""
+
+    def __init__(self, dataset: str, language: str, **kwargs):
+        """BuilderConfig for IE-SemParse.
+
+        Args:
+        language: One of hi, bn, mr, as, ta, te, or, ml, pa, gu, kn
+          **kwargs: keyword arguments forwarded to super.
+        """
+        super(IESemParseConfig, self).__init__(**kwargs)
+
+        self.dataset = dataset
+        self.language = language
+        self.languages = _LANGUAGES
+        self.datasets = _DATASETS
+
+        self._URLS = [os.path.join(
+            _URL, "unfiltered_data", dataset, f"{language}.json")]
+
+
+class IE-SemParse(datasets.GeneratorBasedBuilder):
+    """IE-SemParse: Inter-Bilingual Semantic Parsing Dataset for Indic Languages. Version 1.0."""
+
+    VERSION = datasets.Version("1.0.0", "")
+    BUILDER_CONFIG_CLASS = IESemParseConfig
+    BUILDER_CONFIGS = [
+        IESemParseConfig(
+            name=f"{dataset}_{language}",
+            language=language,
+            dataset=dataset,
+            version=datasets.Version("1.0.0", ""),
+            description=f"Plain text import of IE-SemParse for the {language} language for {dataset} dataset",
+        )
+        for language, dataset in zip(_LANGUAGES, _DATASETS)
+    ]
+
+    def _info(self):
+        dl_manager = datasets.DownloadManager()
+
+        urls_to_download = self.config._URLS
+
+        filepath = dl_manager.download_and_extract(urls_to_download)[0]
+
+        with open(filepath, "r") as f:
+            data = json.load(f)
+            data = data[list(data.keys())[0]]
+
+        features = datasets.Features(
+            {k: datasets.Value("string") for k in data[0].keys()}
+        )
+
+        return datasets.DatasetInfo(
+            description=_DESCRIPTION,
+            features=features,
+            # No default supervised_keys (as we have to pass both premise
+            # and hypothesis as input).
+            supervised_keys=None,
+            homepage="https://github.com/divyanshuaggarwal/IE-SemParse",
+            citation=_CITATION,
+        )
+
+    def _split_generators(self, dl_manager):
+        urls_to_download = self.config._URLS
+
+        downloaded_file = dl_manager.download_and_extract(urls_to_download)[0]
+
+        return [
+            datasets.SplitGenerator(
+                name=datasets.Split.TRAIN,
+                gen_kwargs={
+                    "split_key": "train",
+                    "filepath": downloaded_file,
+                    "data_format": "IE-SemParse"
+                },
+            ),
+            datasets.SplitGenerator(
+                name=datasets.Split.TEST,
+                gen_kwargs={
+                    "split_key": "test",
+                    "filepath": downloaded_file,
+                    "data_format": "IE-SemParse"
+                },
+            ),
+            datasets.SplitGenerator(
+                name=datasets.Split.VALIDATION,
+                gen_kwargs={
+                    "split_key": "val",
+                    "filepath": downloaded_file,
+                    "data_format": "IE-SemParse"
+                },
+            ),
+        ]
+
+    def _generate_examples(self, data_format, split_key, filepath):
+        """This function returns the examples in the raw (text) form."""
+
+        with open(filepath, "r") as f:
+            data = json.load(f)
+            data = data[split_key]
+
+        for idx, row in enumerate(data):
+            yield idx, {
+                k: v for k, v in row.items()
+            }

.history/IE-SemParse_20230707234108.py

@@ -0,0 +1,162 @@
+# coding=utf-8
+
+
+# Lint as: python3
+"""IndicXNLI: The Cross-Lingual NLI Corpus for Indic Languages."""
+
+
+import os
+import json
+
+import pandas as pd
+
+import datasets
+
+from datasets import DownloadManager
+
+
+_CITATION = """\
+@misc{aggarwal2023evaluating,
+      title={Evaluating Inter-Bilingual Semantic Parsing for Indian Languages}, 
+      author={Divyanshu Aggarwal and Vivek Gupta and Anoop Kunchukuttan},
+      year={2023},
+      eprint={2304.13005},
+      archivePrefix={arXiv},
+      primaryClass={cs.CL}
+}
+"""
+
+_DESCRIPTION = """\
+    IE-SemParse is an Inter-bilingual Seq2seq Semantic parsing dataset for 11 distinct Indian languages
+"""
+
+_LANGUAGES = (
+    'hi',
+    'bn',
+    'mr',
+    'as',
+    'ta',
+    'te',
+    'or',
+    'ml',
+    'pa',
+    'gu',
+    'kn'
+)
+
+
+_DATASETS = (
+    'itop',
+    'indic-atis',
+    'indic-TOP'
+)
+
+
+_URL = "https://huggingface.co/datasets/Divyanshu/IE-SemParse/resolve/main/"
+
+
+class IESemParseConfig(datasets.BuilderConfig):
+    """BuilderConfig for IE-SemParse."""
+
+    def __init__(self, dataset: str, language: str, **kwargs):
+        """BuilderConfig for IE-SemParse.
+
+        Args:
+        language: One of hi, bn, mr, as, ta, te, or, ml, pa, gu, kn
+          **kwargs: keyword arguments forwarded to super.
+        """
+        super(IESemParseConfig, self).__init__(**kwargs)
+
+        self.dataset = dataset
+        self.language = language
+        self.languages = _LANGUAGES
+        self.datasets = _DATASETS
+
+        self._URLS = [os.path.join(
+            _URL, "unfiltered_data", dataset, f"{language}.json")]
+
+
+class IE-SemParse(datasets.GeneratorBasedBuilder):
+    """IE-SemParse: Inter-Bilingual Semantic Parsing Dataset for Indic Languages. Version 1.0."""
+
+    VERSION = datasets.Version("1.0.0", "")
+    BUILDER_CONFIG_CLASS = IESemParseConfig
+    BUILDER_CONFIGS = [
+        IESemParseConfig(
+            name=f"{dataset}_{language}",
+            language=language,
+            dataset=dataset,
+            version=datasets.Version("1.0.0", ""),
+            description=f"Plain text import of IE-SemParse for the {language} language for {dataset} dataset",
+        )
+        for language, dataset in zip(_LANGUAGES, _DATASETS)
+    ]
+
+    def _info(self):
+        dl_manager = datasets.DownloadManager()
+
+        urls_to_download = self.config._URLS
+
+        filepath = dl_manager.download_and_extract(urls_to_download)[0]
+
+        with open(filepath, "r") as f:
+            data = json.load(f)
+            data = data[list(data.keys())[0]]
+
+        features = datasets.Features(
+            {k: datasets.Value("string") for k in data[0].keys()}
+        )
+
+        return datasets.DatasetInfo(
+            description=_DESCRIPTION,
+            features=features,
+            # No default supervised_keys (as we have to pass both premise
+            # and hypothesis as input).
+            supervised_keys=None,
+            homepage="https://github.com/divyanshuaggarwal/IE-SemParse",
+            citation=_CITATION,
+        )
+
+    def _split_generators(self, dl_manager):
+        urls_to_download = self.config._URLS
+
+        downloaded_file = dl_manager.download_and_extract(urls_to_download)[0]
+
+        return [
+            datasets.SplitGenerator(
+                name=datasets.Split.TRAIN,
+                gen_kwargs={
+                    "split_key": "train",
+                    "filepath": downloaded_file,
+                    "data_format": "IE-SemParse"
+                },
+            ),
+            datasets.SplitGenerator(
+                name=datasets.Split.TEST,
+                gen_kwargs={
+                    "split_key": "test",
+                    "filepath": downloaded_file,
+                    "data_format": "IE-SemParse"
+                },
+            ),
+            datasets.SplitGenerator(
+                name=datasets.Split.VALIDATION,
+                gen_kwargs={
+                    "split_key": "val",
+                    "filepath": downloaded_file,
+                    "data_format": "IE-SemParse"
+                },
+            ),
+        ]
+
+    def _generate_examples(self, data_format, split_key, filepath):
+        """This function returns the examples in the raw (text) form."""
+
+        with open(filepath, "r") as f:
+            data = json.load(f)
+            data = data[split_key]
+
+        for idx, row in enumerate(data):
+            yield idx, {
+                k: v for k, v in row.items()
+            }

.history/IE-SemParse_20230707234111.py

@@ -0,0 +1,162 @@
+# coding=utf-8
+
+
+# Lint as: python3
+"""IndicXNLI: The Cross-Lingual NLI Corpus for Indic Languages."""
+
+
+import os
+import json
+
+import pandas as pd
+
+import datasets
+
+from datasets import DownloadManager
+
+
+_CITATION = """\
+@misc{aggarwal2023evaluating,
+      title={Evaluating Inter-Bilingual Semantic Parsing for Indian Languages}, 
+      author={Divyanshu Aggarwal and Vivek Gupta and Anoop Kunchukuttan},
+      year={2023},
+      eprint={2304.13005},
+      archivePrefix={arXiv},
+      primaryClass={cs.CL}
+}
+"""
+
+_DESCRIPTION = """\
+    IE-SemParse is an Inter-bilingual Seq2seq Semantic parsing dataset for 11 distinct Indian languages
+"""
+
+_LANGUAGES = (
+    'hi',
+    'bn',
+    'mr',
+    'as',
+    'ta',
+    'te',
+    'or',
+    'ml',
+    'pa',
+    'gu',
+    'kn'
+)
+
+
+_DATASETS = (
+    'itop',
+    'indic-atis',
+    'indic-TOP'
+)
+
+
+_URL = "https://huggingface.co/datasets/Divyanshu/IE-SemParse/resolve/main/"
+
+
+class IESemParseConfig(datasets.BuilderConfig):
+    """BuilderConfig for IE-SemParse."""
+
+    def __init__(self, dataset: str, language: str, **kwargs):
+        """BuilderConfig for IE-SemParse.
+
+        Args:
+        language: One of hi, bn, mr, as, ta, te, or, ml, pa, gu, kn
+          **kwargs: keyword arguments forwarded to super.
+        """
+        super(IESemParseConfig, self).__init__(**kwargs)
+
+        self.dataset = dataset
+        self.language = language
+        self.languages = _LANGUAGES
+        self.datasets = _DATASETS
+
+        self._URLS = [os.path.join(
+            _URL, "unfiltered_data", dataset, f"{language}.json")]
+
+
+class IE_SemParse(datasets.GeneratorBasedBuilder):
+    """IE-SemParse: Inter-Bilingual Semantic Parsing Dataset for Indic Languages. Version 1.0."""
+
+    VERSION = datasets.Version("1.0.0", "")
+    BUILDER_CONFIG_CLASS = IESemParseConfig
+    BUILDER_CONFIGS = [
+        IESemParseConfig(
+            name=f"{dataset}_{language}",
+            language=language,
+            dataset=dataset,
+            version=datasets.Version("1.0.0", ""),
+            description=f"Plain text import of IE-SemParse for the {language} language for {dataset} dataset",
+        )
+        for language, dataset in zip(_LANGUAGES, _DATASETS)
+    ]
+
+    def _info(self):
+        dl_manager = datasets.DownloadManager()
+
+        urls_to_download = self.config._URLS
+
+        filepath = dl_manager.download_and_extract(urls_to_download)[0]
+
+        with open(filepath, "r") as f:
+            data = json.load(f)
+            data = data[list(data.keys())[0]]
+
+        features = datasets.Features(
+            {k: datasets.Value("string") for k in data[0].keys()}
+        )
+
+        return datasets.DatasetInfo(
+            description=_DESCRIPTION,
+            features=features,
+            # No default supervised_keys (as we have to pass both premise
+            # and hypothesis as input).
+            supervised_keys=None,
+            homepage="https://github.com/divyanshuaggarwal/IE-SemParse",
+            citation=_CITATION,
+        )
+
+    def _split_generators(self, dl_manager):
+        urls_to_download = self.config._URLS
+
+        downloaded_file = dl_manager.download_and_extract(urls_to_download)[0]
+
+        return [
+            datasets.SplitGenerator(
+                name=datasets.Split.TRAIN,
+                gen_kwargs={
+                    "split_key": "train",
+                    "filepath": downloaded_file,
+                    "data_format": "IE-SemParse"
+                },
+            ),
+            datasets.SplitGenerator(
+                name=datasets.Split.TEST,
+                gen_kwargs={
+                    "split_key": "test",
+                    "filepath": downloaded_file,
+                    "data_format": "IE-SemParse"
+                },
+            ),
+            datasets.SplitGenerator(
+                name=datasets.Split.VALIDATION,
+                gen_kwargs={
+                    "split_key": "val",
+                    "filepath": downloaded_file,
+                    "data_format": "IE-SemParse"
+                },
+            ),
+        ]
+
+    def _generate_examples(self, data_format, split_key, filepath):
+        """This function returns the examples in the raw (text) form."""
+
+        with open(filepath, "r") as f:
+            data = json.load(f)
+            data = data[split_key]
+
+        for idx, row in enumerate(data):
+            yield idx, {
+                k: v for k, v in row.items()
+            }

.history/IE-SemParse_20230707234114.py

@@ -0,0 +1,162 @@
+# coding=utf-8
+
+
+# Lint as: python3
+"""IndicXNLI: The Cross-Lingual NLI Corpus for Indic Languages."""
+
+
+import os
+import json
+
+import pandas as pd
+
+import datasets
+
+from datasets import DownloadManager
+
+
+_CITATION = """\
+@misc{aggarwal2023evaluating,
+      title={Evaluating Inter-Bilingual Semantic Parsing for Indian Languages}, 
+      author={Divyanshu Aggarwal and Vivek Gupta and Anoop Kunchukuttan},
+      year={2023},
+      eprint={2304.13005},
+      archivePrefix={arXiv},
+      primaryClass={cs.CL}
+}
+"""
+
+_DESCRIPTION = """\
+    IE-SemParse is an Inter-bilingual Seq2seq Semantic parsing dataset for 11 distinct Indian languages
+"""
+
+_LANGUAGES = (
+    'hi',
+    'bn',
+    'mr',
+    'as',
+    'ta',
+    'te',
+    'or',
+    'ml',
+    'pa',
+    'gu',
+    'kn'
+)
+
+
+_DATASETS = (
+    'itop',
+    'indic-atis',
+    'indic-TOP'
+)
+
+
+_URL = "https://huggingface.co/datasets/Divyanshu/IE-SemParse/resolve/main/"
+
+
+class IE_SemParseConfig(datasets.BuilderConfig):
+    """BuilderConfig for IE-SemParse."""
+
+    def __init__(self, dataset: str, language: str, **kwargs):
+        """BuilderConfig for IE-SemParse.
+
+        Args:
+        language: One of hi, bn, mr, as, ta, te, or, ml, pa, gu, kn
+          **kwargs: keyword arguments forwarded to super.
+        """
+        super(IESemParseConfig, self).__init__(**kwargs)
+
+        self.dataset = dataset
+        self.language = language
+        self.languages = _LANGUAGES
+        self.datasets = _DATASETS
+
+        self._URLS = [os.path.join(
+            _URL, "unfiltered_data", dataset, f"{language}.json")]
+
+
+class IE_SemParse(datasets.GeneratorBasedBuilder):
+    """IE-SemParse: Inter-Bilingual Semantic Parsing Dataset for Indic Languages. Version 1.0."""
+
+    VERSION = datasets.Version("1.0.0", "")
+    BUILDER_CONFIG_CLASS = IESemParseConfig
+    BUILDER_CONFIGS = [
+        IESemParseConfig(
+            name=f"{dataset}_{language}",
+            language=language,
+            dataset=dataset,
+            version=datasets.Version("1.0.0", ""),
+            description=f"Plain text import of IE-SemParse for the {language} language for {dataset} dataset",
+        )
+        for language, dataset in zip(_LANGUAGES, _DATASETS)
+    ]
+
+    def _info(self):
+        dl_manager = datasets.DownloadManager()
+
+        urls_to_download = self.config._URLS
+
+        filepath = dl_manager.download_and_extract(urls_to_download)[0]
+
+        with open(filepath, "r") as f:
+            data = json.load(f)
+            data = data[list(data.keys())[0]]
+
+        features = datasets.Features(
+            {k: datasets.Value("string") for k in data[0].keys()}
+        )
+
+        return datasets.DatasetInfo(
+            description=_DESCRIPTION,
+            features=features,
+            # No default supervised_keys (as we have to pass both premise
+            # and hypothesis as input).
+            supervised_keys=None,
+            homepage="https://github.com/divyanshuaggarwal/IE-SemParse",
+            citation=_CITATION,
+        )
+
+    def _split_generators(self, dl_manager):
+        urls_to_download = self.config._URLS
+
+        downloaded_file = dl_manager.download_and_extract(urls_to_download)[0]
+
+        return [
+            datasets.SplitGenerator(
+                name=datasets.Split.TRAIN,
+                gen_kwargs={
+                    "split_key": "train",
+                    "filepath": downloaded_file,
+                    "data_format": "IE-SemParse"
+                },
+            ),
+            datasets.SplitGenerator(
+                name=datasets.Split.TEST,
+                gen_kwargs={
+                    "split_key": "test",
+                    "filepath": downloaded_file,
+                    "data_format": "IE-SemParse"
+                },
+            ),
+            datasets.SplitGenerator(
+                name=datasets.Split.VALIDATION,
+                gen_kwargs={
+                    "split_key": "val",
+                    "filepath": downloaded_file,
+                    "data_format": "IE-SemParse"
+                },
+            ),
+        ]
+
+    def _generate_examples(self, data_format, split_key, filepath):
+        """This function returns the examples in the raw (text) form."""
+
+        with open(filepath, "r") as f:
+            data = json.load(f)
+            data = data[split_key]
+
+        for idx, row in enumerate(data):
+            yield idx, {
+                k: v for k, v in row.items()
+            }

.history/IE-SemParse_20230707234133.py

@@ -0,0 +1,162 @@
+# coding=utf-8
+
+
+# Lint as: python3
+"""IndicXNLI: The Cross-Lingual NLI Corpus for Indic Languages."""
+
+
+import os
+import json
+
+import pandas as pd
+
+import datasets
+
+from datasets import DownloadManager
+
+
+_CITATION = """\
+@misc{aggarwal2023evaluating,
+      title={Evaluating Inter-Bilingual Semantic Parsing for Indian Languages}, 
+      author={Divyanshu Aggarwal and Vivek Gupta and Anoop Kunchukuttan},
+      year={2023},
+      eprint={2304.13005},
+      archivePrefix={arXiv},
+      primaryClass={cs.CL}
+}
+"""
+
+_DESCRIPTION = """\
+    IE-SemParse is an Inter-bilingual Seq2seq Semantic parsing dataset for 11 distinct Indian languages
+"""
+
+_LANGUAGES = (
+    'hi',
+    'bn',
+    'mr',
+    'as',
+    'ta',
+    'te',
+    'or',
+    'ml',
+    'pa',
+    'gu',
+    'kn'
+)
+
+
+_DATASETS = (
+    'itop',
+    'indic-atis',
+    'indic-TOP'
+)
+
+
+_URL = "https://huggingface.co/datasets/Divyanshu/IE-SemParse/resolve/main/"
+
+
+class IE_SemParseConfig(datasets.BuilderConfig):
+    """BuilderConfig for IE-SemParse."""
+
+    def __init__(self, dataset: str, language: str, **kwargs):
+        """BuilderConfig for IE-SemParse.
+
+        Args:
+        language: One of hi, bn, mr, as, ta, te, or, ml, pa, gu, kn
+          **kwargs: keyword arguments forwarded to super.
+        """
+        super(IE_SemParseConfig, self).__init__(**kwargs)
+
+        self.dataset = dataset
+        self.language = language
+        self.languages = _LANGUAGES
+        self.datasets = _DATASETS
+
+        self._URLS = [os.path.join(
+            _URL, "unfiltered_data", dataset, f"{language}.json")]
+
+
+class IE_SemParse(datasets.GeneratorBasedBuilder):
+    """IE-SemParse: Inter-Bilingual Semantic Parsing Dataset for Indic Languages. Version 1.0."""
+
+    VERSION = datasets.Version("1.0.0", "")
+    BUILDER_CONFIG_CLASS = IESemParseConfig
+    BUILDER_CONFIGS = [
+        IESemParseConfig(
+            name=f"{dataset}_{language}",
+            language=language,
+            dataset=dataset,
+            version=datasets.Version("1.0.0", ""),
+            description=f"Plain text import of IE-SemParse for the {language} language for {dataset} dataset",
+        )
+        for language, dataset in zip(_LANGUAGES, _DATASETS)
+    ]
+
+    def _info(self):
+        dl_manager = datasets.DownloadManager()
+
+        urls_to_download = self.config._URLS
+
+        filepath = dl_manager.download_and_extract(urls_to_download)[0]
+
+        with open(filepath, "r") as f:
+            data = json.load(f)
+            data = data[list(data.keys())[0]]
+
+        features = datasets.Features(
+            {k: datasets.Value("string") for k in data[0].keys()}
+        )
+
+        return datasets.DatasetInfo(
+            description=_DESCRIPTION,
+            features=features,
+            # No default supervised_keys (as we have to pass both premise
+            # and hypothesis as input).
+            supervised_keys=None,
+            homepage="https://github.com/divyanshuaggarwal/IE-SemParse",
+            citation=_CITATION,
+        )
+
+    def _split_generators(self, dl_manager):
+        urls_to_download = self.config._URLS
+
+        downloaded_file = dl_manager.download_and_extract(urls_to_download)[0]
+
+        return [
+            datasets.SplitGenerator(
+                name=datasets.Split.TRAIN,
+                gen_kwargs={
+                    "split_key": "train",
+                    "filepath": downloaded_file,
+                    "data_format": "IE-SemParse"
+                },
+            ),
+            datasets.SplitGenerator(
+                name=datasets.Split.TEST,
+                gen_kwargs={
+                    "split_key": "test",
+                    "filepath": downloaded_file,
+                    "data_format": "IE-SemParse"
+                },
+            ),
+            datasets.SplitGenerator(
+                name=datasets.Split.VALIDATION,
+                gen_kwargs={
+                    "split_key": "val",
+                    "filepath": downloaded_file,
+                    "data_format": "IE-SemParse"
+                },
+            ),
+        ]
+
+    def _generate_examples(self, data_format, split_key, filepath):
+        """This function returns the examples in the raw (text) form."""
+
+        with open(filepath, "r") as f:
+            data = json.load(f)
+            data = data[split_key]
+
+        for idx, row in enumerate(data):
+            yield idx, {
+                k: v for k, v in row.items()
+            }

.history/IE-SemParse_20230707234139.py

@@ -0,0 +1,162 @@
+# coding=utf-8
+
+
+# Lint as: python3
+"""IndicXNLI: The Cross-Lingual NLI Corpus for Indic Languages."""
+
+
+import os
+import json
+
+import pandas as pd
+
+import datasets
+
+from datasets import DownloadManager
+
+
+_CITATION = """\
+@misc{aggarwal2023evaluating,
+      title={Evaluating Inter-Bilingual Semantic Parsing for Indian Languages}, 
+      author={Divyanshu Aggarwal and Vivek Gupta and Anoop Kunchukuttan},
+      year={2023},
+      eprint={2304.13005},
+      archivePrefix={arXiv},
+      primaryClass={cs.CL}
+}
+"""
+
+_DESCRIPTION = """\
+    IE-SemParse is an Inter-bilingual Seq2seq Semantic parsing dataset for 11 distinct Indian languages
+"""
+
+_LANGUAGES = (
+    'hi',
+    'bn',
+    'mr',
+    'as',
+    'ta',
+    'te',
+    'or',
+    'ml',
+    'pa',
+    'gu',
+    'kn'
+)
+
+
+_DATASETS = (
+    'itop',
+    'indic-atis',
+    'indic-TOP'
+)
+
+
+_URL = "https://huggingface.co/datasets/Divyanshu/IE-SemParse/resolve/main/"
+
+
+class IE_SemParseConfig(datasets.BuilderConfig):
+    """BuilderConfig for IE-SemParse."""
+
+    def __init__(self, dataset: str, language: str, **kwargs):
+        """BuilderConfig for IE-SemParse.
+
+        Args:
+        language: One of hi, bn, mr, as, ta, te, or, ml, pa, gu, kn
+          **kwargs: keyword arguments forwarded to super.
+        """
+        super(IE_SemParseConfig, self).__init__(**kwargs)
+
+        self.dataset = dataset
+        self.language = language
+        self.languages = _LANGUAGES
+        self.datasets = _DATASETS
+
+        self._URLS = [os.path.join(
+            _URL, "unfiltered_data", dataset, f"{language}.json")]
+
+
+class IE_SemParse(datasets.GeneratorBasedBuilder):
+    """IE-SemParse: Inter-Bilingual Semantic Parsing Dataset for Indic Languages. Version 1.0."""
+
+    VERSION = datasets.Version("1.0.0", "")
+    BUILDER_CONFIG_CLASS = IE_SemParseConfig
+    BUILDER_CONFIGS = [
+        IESemParseConfig(
+            name=f"{dataset}_{language}",
+            language=language,
+            dataset=dataset,
+            version=datasets.Version("1.0.0", ""),
+            description=f"Plain text import of IE-SemParse for the {language} language for {dataset} dataset",
+        )
+        for language, dataset in zip(_LANGUAGES, _DATASETS)
+    ]
+
+    def _info(self):
+        dl_manager = datasets.DownloadManager()
+
+        urls_to_download = self.config._URLS
+
+        filepath = dl_manager.download_and_extract(urls_to_download)[0]
+
+        with open(filepath, "r") as f:
+            data = json.load(f)
+            data = data[list(data.keys())[0]]
+
+        features = datasets.Features(
+            {k: datasets.Value("string") for k in data[0].keys()}
+        )
+
+        return datasets.DatasetInfo(
+            description=_DESCRIPTION,
+            features=features,
+            # No default supervised_keys (as we have to pass both premise
+            # and hypothesis as input).
+            supervised_keys=None,
+            homepage="https://github.com/divyanshuaggarwal/IE-SemParse",
+            citation=_CITATION,
+        )
+
+    def _split_generators(self, dl_manager):
+        urls_to_download = self.config._URLS
+
+        downloaded_file = dl_manager.download_and_extract(urls_to_download)[0]
+
+        return [
+            datasets.SplitGenerator(
+                name=datasets.Split.TRAIN,
+                gen_kwargs={
+                    "split_key": "train",
+                    "filepath": downloaded_file,
+                    "data_format": "IE-SemParse"
+                },
+            ),
+            datasets.SplitGenerator(
+                name=datasets.Split.TEST,
+                gen_kwargs={
+                    "split_key": "test",
+                    "filepath": downloaded_file,
+                    "data_format": "IE-SemParse"
+                },
+            ),
+            datasets.SplitGenerator(
+                name=datasets.Split.VALIDATION,
+                gen_kwargs={
+                    "split_key": "val",
+                    "filepath": downloaded_file,
+                    "data_format": "IE-SemParse"
+                },
+            ),
+        ]
+
+    def _generate_examples(self, data_format, split_key, filepath):
+        """This function returns the examples in the raw (text) form."""
+
+        with open(filepath, "r") as f:
+            data = json.load(f)
+            data = data[split_key]
+
+        for idx, row in enumerate(data):
+            yield idx, {
+                k: v for k, v in row.items()
+            }

.history/IE-SemParse_20230707234141.py

@@ -0,0 +1,162 @@
+# coding=utf-8
+
+
+# Lint as: python3
+"""IndicXNLI: The Cross-Lingual NLI Corpus for Indic Languages."""
+
+
+import os
+import json
+
+import pandas as pd
+
+import datasets
+
+from datasets import DownloadManager
+
+
+_CITATION = """\
+@misc{aggarwal2023evaluating,
+      title={Evaluating Inter-Bilingual Semantic Parsing for Indian Languages}, 
+      author={Divyanshu Aggarwal and Vivek Gupta and Anoop Kunchukuttan},
+      year={2023},
+      eprint={2304.13005},
+      archivePrefix={arXiv},
+      primaryClass={cs.CL}
+}
+"""
+
+_DESCRIPTION = """\
+    IE-SemParse is an Inter-bilingual Seq2seq Semantic parsing dataset for 11 distinct Indian languages
+"""
+
+_LANGUAGES = (
+    'hi',
+    'bn',
+    'mr',
+    'as',
+    'ta',
+    'te',
+    'or',
+    'ml',
+    'pa',
+    'gu',
+    'kn'
+)
+
+
+_DATASETS = (
+    'itop',
+    'indic-atis',
+    'indic-TOP'
+)
+
+
+_URL = "https://huggingface.co/datasets/Divyanshu/IE-SemParse/resolve/main/"
+
+
+class IE_SemParseConfig(datasets.BuilderConfig):
+    """BuilderConfig for IE-SemParse."""
+
+    def __init__(self, dataset: str, language: str, **kwargs):
+        """BuilderConfig for IE-SemParse.
+
+        Args:
+        language: One of hi, bn, mr, as, ta, te, or, ml, pa, gu, kn
+          **kwargs: keyword arguments forwarded to super.
+        """
+        super(IE_SemParseConfig, self).__init__(**kwargs)
+
+        self.dataset = dataset
+        self.language = language
+        self.languages = _LANGUAGES
+        self.datasets = _DATASETS
+
+        self._URLS = [os.path.join(
+            _URL, "unfiltered_data", dataset, f"{language}.json")]
+
+
+class IE_SemParse(datasets.GeneratorBasedBuilder):
+    """IE-SemParse: Inter-Bilingual Semantic Parsing Dataset for Indic Languages. Version 1.0."""
+
+    VERSION = datasets.Version("1.0.0", "")
+    BUILDER_CONFIG_CLASS = IE_SemParseConfig
+    BUILDER_CONFIGS = [
+        IE_SemParseConfig(
+            name=f"{dataset}_{language}",
+            language=language,
+            dataset=dataset,
+            version=datasets.Version("1.0.0", ""),
+            description=f"Plain text import of IE-SemParse for the {language} language for {dataset} dataset",
+        )
+        for language, dataset in zip(_LANGUAGES, _DATASETS)
+    ]
+
+    def _info(self):
+        dl_manager = datasets.DownloadManager()
+
+        urls_to_download = self.config._URLS
+
+        filepath = dl_manager.download_and_extract(urls_to_download)[0]
+
+        with open(filepath, "r") as f:
+            data = json.load(f)
+            data = data[list(data.keys())[0]]
+
+        features = datasets.Features(
+            {k: datasets.Value("string") for k in data[0].keys()}
+        )
+
+        return datasets.DatasetInfo(
+            description=_DESCRIPTION,
+            features=features,
+            # No default supervised_keys (as we have to pass both premise
+            # and hypothesis as input).
+            supervised_keys=None,
+            homepage="https://github.com/divyanshuaggarwal/IE-SemParse",
+            citation=_CITATION,
+        )
+
+    def _split_generators(self, dl_manager):
+        urls_to_download = self.config._URLS
+
+        downloaded_file = dl_manager.download_and_extract(urls_to_download)[0]
+
+        return [
+            datasets.SplitGenerator(
+                name=datasets.Split.TRAIN,
+                gen_kwargs={
+                    "split_key": "train",
+                    "filepath": downloaded_file,
+                    "data_format": "IE-SemParse"
+                },
+            ),
+            datasets.SplitGenerator(
+                name=datasets.Split.TEST,
+                gen_kwargs={
+                    "split_key": "test",
+                    "filepath": downloaded_file,
+                    "data_format": "IE-SemParse"
+                },
+            ),
+            datasets.SplitGenerator(
+                name=datasets.Split.VALIDATION,
+                gen_kwargs={
+                    "split_key": "val",
+                    "filepath": downloaded_file,
+                    "data_format": "IE-SemParse"
+                },
+            ),
+        ]
+
+    def _generate_examples(self, data_format, split_key, filepath):
+        """This function returns the examples in the raw (text) form."""
+
+        with open(filepath, "r") as f:
+            data = json.load(f)
+            data = data[split_key]
+
+        for idx, row in enumerate(data):
+            yield idx, {
+                k: v for k, v in row.items()
+            }

.history/IE-SemParse_20230707234143.py

@@ -0,0 +1,162 @@
+# coding=utf-8
+
+
+# Lint as: python3
+"""IndicXNLI: The Cross-Lingual NLI Corpus for Indic Languages."""
+
+
+import os
+import json
+
+import pandas as pd
+
+import datasets
+
+from datasets import DownloadManager
+
+
+_CITATION = """\
+@misc{aggarwal2023evaluating,
+      title={Evaluating Inter-Bilingual Semantic Parsing for Indian Languages}, 
+      author={Divyanshu Aggarwal and Vivek Gupta and Anoop Kunchukuttan},
+      year={2023},
+      eprint={2304.13005},
+      archivePrefix={arXiv},
+      primaryClass={cs.CL}
+}
+"""
+
+_DESCRIPTION = """\
+    IE-SemParse is an Inter-bilingual Seq2seq Semantic parsing dataset for 11 distinct Indian languages
+"""
+
+_LANGUAGES = (
+    'hi',
+    'bn',
+    'mr',
+    'as',
+    'ta',
+    'te',
+    'or',
+    'ml',
+    'pa',
+    'gu',
+    'kn'
+)
+
+
+_DATASETS = (
+    'itop',
+    'indic-atis',
+    'indic-TOP'
+)
+
+
+_URL = "https://huggingface.co/datasets/Divyanshu/IE-SemParse/resolve/main/"
+
+
+class IE_SemParseConfig(datasets.BuilderConfig):
+    """BuilderConfig for IE-SemParse."""
+
+    def __init__(self, dataset: str, language: str, **kwargs):
+        """BuilderConfig for IE-SemParse.
+
+        Args:
+        language: One of hi, bn, mr, as, ta, te, or, ml, pa, gu, kn
+          **kwargs: keyword arguments forwarded to super.
+        """
+        super(IE_SemParseConfig, self).__init__(**kwargs)
+
+        self.dataset = dataset
+        self.language = language
+        self.languages = _LANGUAGES
+        self.datasets = _DATASETS
+
+        self._URLS = [os.path.join(
+            _URL, "unfiltered_data", dataset, f"{language}.json")]
+
+
+class IE_SemParse(datasets.GeneratorBasedBuilder):
+    """IE-SemParse: Inter-Bilingual Semantic Parsing Dataset for Indic Languages. Version 1.0."""
+
+    VERSION = datasets.Version("1.0.0", "")
+    BUILDER_CONFIG_CLASS = IE_SemParseConfig
+    BUILDER_CONFIGS = [
+        IE_SemParseConfig(
+            name=f"{dataset}_{language}",
+            language=language,
+            dataset=dataset,
+            version=datasets.Version("1.0.0", ""),
+            description=f"Plain text import of IE-SemParse for the {language} language for {dataset} dataset",
+        )
+        for language, dataset in zip(_LANGUAGES, _DATASETS)
+    ]
+
+    def _info(self):
+        dl_manager = datasets.DownloadManager()
+
+        urls_to_download = self.config._URLS
+
+        filepath = dl_manager.download_and_extract(urls_to_download)[0]
+
+        with open(filepath, "r") as f:
+            data = json.load(f)
+            data = data[list(data.keys())[0]]
+
+        features = datasets.Features(
+            {k: datasets.Value("string") for k in data[0].keys()}
+        )
+
+        return datasets.DatasetInfo(
+            description=_DESCRIPTION,
+            features=features,
+            # No default supervised_keys (as we have to pass both premise
+            # and hypothesis as input).
+            supervised_keys=None,
+            homepage="https://github.com/divyanshuaggarwal/IE-SemParse",
+            citation=_CITATION,
+        )
+
+    def _split_generators(self, dl_manager):
+        urls_to_download = self.config._URLS
+
+        downloaded_file = dl_manager.download_and_extract(urls_to_download)[0]
+
+        return [
+            datasets.SplitGenerator(
+                name=datasets.Split.TRAIN,
+                gen_kwargs={
+                    "split_key": "train",
+                    "filepath": downloaded_file,
+                    "data_format": "IE-SemParse"
+                },
+            ),
+            datasets.SplitGenerator(
+                name=datasets.Split.TEST,
+                gen_kwargs={
+                    "split_key": "test",
+                    "filepath": downloaded_file,
+                    "data_format": "IE-SemParse"
+                },
+            ),
+            datasets.SplitGenerator(
+                name=datasets.Split.VALIDATION,
+                gen_kwargs={
+                    "split_key": "val",
+                    "filepath": downloaded_file,
+                    "data_format": "IE-SemParse"
+                },
+            ),
+        ]
+
+    def _generate_examples(self, data_format, split_key, filepath):
+        """This function returns the examples in the raw (text) form."""
+
+        with open(filepath, "r") as f:
+            data = json.load(f)
+            data = data[split_key]
+
+        for idx, row in enumerate(data):
+            yield idx, {
+                k: v for k, v in row.items()
+            }

.history/README_20230707215813.md

@@ -0,0 +1,3 @@
+---
+license: mit
+---

.history/README_20230707233453.md

@@ -0,0 +1,234 @@
+---
+annotations_creators:
+- machine-generated
+language_creators:
+- machine-generated
+language:
+- as
+- bn
+- gu
+- hi
+- kn
+- ml
+- mr
+- or
+- pa
+- ta
+- te
+license:
+- cc0-1.0
+multilinguality:
+- multilingual
+pretty_name: IndicXNLI
+size_categories:
+- 1M<n<10M
+source_datasets:
+- original
+task_categories:
+- text-classification
+task_ids:
+- natural-language-inference
+---
+
+# Dataset Card for "IndicXNLI"
+
+## Table of Contents
+
+- [Dataset Card for "IndicXNLI"](#dataset-card-for-indicxnli)
+  - [Table of Contents](#table-of-contents)
+  - [Dataset Description](#dataset-description)
+    - [Dataset Summary](#dataset-summary)
+    - [Supported Tasks and Leaderboards](#supported-tasks-and-leaderboards)
+    - [Languages](#languages)
+  - [Dataset Structure](#dataset-structure)
+    - [Data Instances](#data-instances)
+    - [Data Fields](#data-fields)
+    - [Data Splits](#data-splits)
+  - [Dataset usage](#dataset-usage)
+  - [Dataset Creation](#dataset-creation)
+    - [Curation Rationale](#curation-rationale)
+    - [Source Data](#source-data)
+      - [Initial Data Collection and Normalization](#initial-data-collection-and-normalization)
+      - [Who are the source language producers?](#who-are-the-source-language-producers)
+      - [Human Verification Process](#human-verification-process)
+  - [Considerations for Using the Data](#considerations-for-using-the-data)
+    - [Social Impact of Dataset](#social-impact-of-dataset)
+    - [Discussion of Biases](#discussion-of-biases)
+    - [Other Known Limitations](#other-known-limitations)
+    - [Dataset Curators](#dataset-curators)
+    - [Licensing Information](#licensing-information)
+    - [Citation Information](#citation-information)
+
+## Dataset Description
+
+- **Homepage:** <https://github.com/divyanshuaggarwal/IndicXNLI>
+- **Paper:** [IndicXNLI: Evaluating Multilingual Inference for Indian Languages](https://arxiv.org/abs/2204.08776)
+- **Point of Contact:** [Divyanshu Aggarwal](mailto:[email protected])
+
+### Dataset Summary
+
+INDICXNLI is similar to existing
+XNLI dataset in shape/form, but focusses on Indic language family. INDICXNLI include NLI
+data for eleven major Indic languages that includes
+Assamese (‘as’), Gujarat (‘gu’), Kannada (‘kn’),
+Malayalam (‘ml’), Marathi (‘mr’), Odia (‘or’),
+Punjabi (‘pa’), Tamil (‘ta’), Telugu (‘te’), Hindi
+(‘hi’), and Bengali (‘bn’).
+
+### Supported Tasks and Leaderboards
+
+**Tasks:** Natural Language Inference
+
+**Leaderboards:** Currently there is no Leaderboard for this dataset.
+
+### Languages
+
+- `Assamese (as)`
+- `Bengali (bn)`
+- `Gujarati (gu)`
+- `Kannada (kn)`
+- `Hindi (hi)`
+- `Malayalam (ml)`
+- `Marathi (mr)`
+- `Oriya (or)`
+- `Punjabi (pa)`
+- `Tamil (ta)`
+- `Telugu (te)`
+
+## Dataset Structure
+
+### Data Instances
+
+One example from the `hi` dataset is given below in JSON format.
+
+  ```python
+ {'premise': 'अवधारणात्मक रूप से क्रीम स्किमिंग के दो बुनियादी आयाम हैं-उत्पाद और भूगोल।',
+ 'hypothesis': 'उत्पाद और भूगोल क्रीम स्किमिंग का काम करते हैं।',
+ 'label': 1 (neutral) }
+  ```
+
+### Data Fields
+
+- `premise (string)`: Premise Sentence
+- `hypothesis (string)`: Hypothesis Sentence
+- `label (integer)`: Integer label `0` if hypothesis `entails` the premise, `2` if hypothesis `negates` the premise and `1` otherwise.
+
+### Data Splits
+
+<!-- Below is the dataset split given for `hi` dataset.
+
+```python
+DatasetDict({
+    train: Dataset({
+        features: ['premise', 'hypothesis', 'label'],
+        num_rows: 392702
+    })
+    test: Dataset({
+        features: ['premise', 'hypothesis', 'label'],
+        num_rows: 5010
+    })
+    validation: Dataset({
+        features: ['premise', 'hypothesis', 'label'],
+        num_rows: 2490
+    })
+})
+
+``` -->
+
+Language      | ISO 639-1 Code |Train | Dev | Test |
+--------------|----------------|-------|-----|------|
+Assamese | as | 392,702 | 5,010 | 2,490 |
+Bengali | bn | 392,702 | 5,010 | 2,490 |
+Gujarati | gu |  392,702 | 5,010 | 2,490 |
+Hindi | hi | 392,702 | 5,010 | 2,490 |
+Kannada | kn |  392,702 | 5,010 | 2,490 |
+Malayalam | ml |392,702  | 5,010 | 2,490 |
+Marathi | mr |392,702 | 5,010 | 2,490 |
+Oriya | or | 392,702 | 5,010 | 2,490 |
+Punjabi | pa | 392,702 | 5,010 | 2,490 |
+Tamil | ta | 392,702 | 5,010 | 2,490 |
+Telugu | te | 392,702 | 5,010 | 2,490 |
+
+<!-- The dataset split remains same across all languages. -->
+
+## Dataset usage
+
+Code snippet for using the dataset using datasets library.
+
+```python
+from datasets import load_dataset
+
+dataset = load_dataset("Divyanshu/indicxnli")
+```
+
+## Dataset Creation
+
+Machine translation of XNLI english dataset to 11 listed Indic Languages.
+
+### Curation Rationale
+
+[More information needed]
+
+### Source Data
+
+[XNLI dataset](https://cims.nyu.edu/~sbowman/xnli/)
+
+#### Initial Data Collection and Normalization
+
+[Detailed in the paper](https://arxiv.org/abs/2204.08776)
+
+#### Who are the source language producers?
+
+[Detailed in the paper](https://arxiv.org/abs/2204.08776)
+
+#### Human Verification Process
+
+[Detailed in the paper](https://arxiv.org/abs/2204.08776)
+
+## Considerations for Using the Data
+
+### Social Impact of Dataset
+
+[Detailed in the paper](https://arxiv.org/abs/2204.08776)
+
+### Discussion of Biases
+
+[Detailed in the paper](https://arxiv.org/abs/2204.08776)
+
+### Other Known Limitations
+
+[Detailed in the paper](https://arxiv.org/abs/2204.08776)
+
+### Dataset Curators
+
+Divyanshu Aggarwal, Vivek Gupta, Anoop Kunchukuttan
+
+### Licensing Information
+
+Contents of this repository are restricted to only non-commercial research purposes under the [Creative Commons Attribution-NonCommercial 4.0 International License (CC BY-NC 4.0)](https://creativecommons.org/licenses/by-nc/4.0/). Copyright of the dataset contents belongs to the original copyright holders.
+
+### Citation Information
+
+If you use any of the datasets, models or code modules, please cite the following paper:
+
+```
+@misc{https://doi.org/10.48550/arxiv.2204.08776,
+  doi = {10.48550/ARXIV.2204.08776},
+  
+  url = {https://arxiv.org/abs/2204.08776},
+  
+  author = {Aggarwal, Divyanshu and Gupta, Vivek and Kunchukuttan, Anoop},
+  
+  keywords = {Computation and Language (cs.CL), Artificial Intelligence (cs.AI), FOS: Computer and information sciences, FOS: Computer and information sciences},
+  
+  title = {IndicXNLI: Evaluating Multilingual Inference for Indian Languages}, 
+  
+  publisher = {arXiv},
+  
+  year = {2022},
+  
+  copyright = {Creative Commons Attribution 4.0 International}
+}
+```
+
+<!-- ### Contributions -->

.history/README_20230707233505.md

@@ -0,0 +1,234 @@
+---
+annotations_creators:
+- machine-generated
+language_creators:
+- machine-generated
+language:
+- as
+- bn
+- gu
+- hi
+- kn
+- ml
+- mr
+- or
+- pa
+- ta
+- te
+license:
+- cc0-1.0
+multilinguality:
+- multilingual
+pretty_name: IndicXNLI
+size_categories:
+- 1M<n<10M
+source_datasets:
+- original
+task_categories:
+- text-classification
+task_ids:
+- natural-language-inference
+---
+
+# Dataset Card for "IndicXNLI"
+
+## Table of Contents
+
+- [Dataset Card for "IndicXNLI"](#dataset-card-for-indicxnli)
+  - [Table of Contents](#table-of-contents)
+  - [Dataset Description](#dataset-description)
+    - [Dataset Summary](#dataset-summary)
+    - [Supported Tasks and Leaderboards](#supported-tasks-and-leaderboards)
+    - [Languages](#languages)
+  - [Dataset Structure](#dataset-structure)
+    - [Data Instances](#data-instances)
+    - [Data Fields](#data-fields)
+    - [Data Splits](#data-splits)
+  - [Dataset usage](#dataset-usage)
+  - [Dataset Creation](#dataset-creation)
+    - [Curation Rationale](#curation-rationale)
+    - [Source Data](#source-data)
+      - [Initial Data Collection and Normalization](#initial-data-collection-and-normalization)
+      - [Who are the source language producers?](#who-are-the-source-language-producers)
+      - [Human Verification Process](#human-verification-process)
+  - [Considerations for Using the Data](#considerations-for-using-the-data)
+    - [Social Impact of Dataset](#social-impact-of-dataset)
+    - [Discussion of Biases](#discussion-of-biases)
+    - [Other Known Limitations](#other-known-limitations)
+    - [Dataset Curators](#dataset-curators)
+    - [Licensing Information](#licensing-information)
+    - [Citation Information](#citation-information)
+
+## Dataset Description
+
+- **Homepage:** <https://github.com/divyanshuaggarwal/IndicXNLI>
+- **Paper:** [IndicXNLI: Evaluating Multilingual Inference for Indian Languages](https://arxiv.org/abs/2204.08776)
+- **Point of Contact:** [Divyanshu Aggarwal](mailto:[email protected])
+
+### Dataset Summary
+
+INDICXNLI is similar to existing
+XNLI dataset in shape/form, but focusses on Indic language family. INDICXNLI include NLI
+data for eleven major Indic languages that includes
+Assamese (‘as’), Gujarat (‘gu’), Kannada (‘kn’),
+Malayalam (‘ml’), Marathi (‘mr’), Odia (‘or’),
+Punjabi (‘pa’), Tamil (‘ta’), Telugu (‘te’), Hindi
+(‘hi’), and Bengali (‘bn’).
+
+### Supported Tasks and Leaderboards
+
+**Tasks:** Natural Language Inference
+
+**Leaderboards:** Currently there is no Leaderboard for this dataset.
+
+### Languages
+
+- `Assamese (as)`
+- `Bengali (bn)`
+- `Gujarati (gu)`
+- `Kannada (kn)`
+- `Hindi (hi)`
+- `Malayalam (ml)`
+- `Marathi (mr)`
+- `Oriya (or)`
+- `Punjabi (pa)`
+- `Tamil (ta)`
+- `Telugu (te)`
+
+## Dataset Structure
+
+### Data Instances
+
+One example from the `hi` dataset is given below in JSON format.
+
+  ```python
+ {'premise': 'अवधारणात्मक रूप से क्रीम स्किमिंग के दो बुनियादी आयाम हैं-उत्पाद और भूगोल।',
+ 'hypothesis': 'उत्पाद और भूगोल क्रीम स्किमिंग का काम करते हैं।',
+ 'label': 1 (neutral) }
+  ```
+
+### Data Fields
+
+- `premise (string)`: Premise Sentence
+- `hypothesis (string)`: Hypothesis Sentence
+- `label (integer)`: Integer label `0` if hypothesis `entails` the premise, `2` if hypothesis `negates` the premise and `1` otherwise.
+
+### Data Splits
+
+<!-- Below is the dataset split given for `hi` dataset.
+
+```python
+DatasetDict({
+    train: Dataset({
+        features: ['premise', 'hypothesis', 'label'],
+        num_rows: 392702
+    })
+    test: Dataset({
+        features: ['premise', 'hypothesis', 'label'],
+        num_rows: 5010
+    })
+    validation: Dataset({
+        features: ['premise', 'hypothesis', 'label'],
+        num_rows: 2490
+    })
+})
+
+``` -->
+
+Language      | ISO 639-1 Code |Train | Dev | Test |
+--------------|----------------|-------|-----|------|
+Assamese | as | 392,702 | 5,010 | 2,490 |
+Bengali | bn | 392,702 | 5,010 | 2,490 |
+Gujarati | gu |  392,702 | 5,010 | 2,490 |
+Hindi | hi | 392,702 | 5,010 | 2,490 |
+Kannada | kn |  392,702 | 5,010 | 2,490 |
+Malayalam | ml |392,702  | 5,010 | 2,490 |
+Marathi | mr |392,702 | 5,010 | 2,490 |
+Oriya | or | 392,702 | 5,010 | 2,490 |
+Punjabi | pa | 392,702 | 5,010 | 2,490 |
+Tamil | ta | 392,702 | 5,010 | 2,490 |
+Telugu | te | 392,702 | 5,010 | 2,490 |
+
+<!-- The dataset split remains same across all languages. -->
+
+## Dataset usage
+
+Code snippet for using the dataset using datasets library.
+
+```python
+from datasets import load_dataset
+
+dataset = load_dataset("Divyanshu/indicxnli")
+```
+
+## Dataset Creation
+
+Machine translation of XNLI english dataset to 11 listed Indic Languages.
+
+### Curation Rationale
+
+[More information needed]
+
+### Source Data
+
+[XNLI dataset](https://cims.nyu.edu/~sbowman/xnli/)
+
+#### Initial Data Collection and Normalization
+
+[Detailed in the paper](https://arxiv.org/abs/2204.08776)
+
+#### Who are the source language producers?
+
+[Detailed in the paper](https://arxiv.org/abs/2204.08776)
+
+#### Human Verification Process
+
+[Detailed in the paper](https://arxiv.org/abs/2204.08776)
+
+## Considerations for Using the Data
+
+### Social Impact of Dataset
+
+[Detailed in the paper](https://arxiv.org/abs/2204.08776)
+
+### Discussion of Biases
+
+[Detailed in the paper](https://arxiv.org/abs/2204.08776)
+
+### Other Known Limitations
+
+[Detailed in the paper](https://arxiv.org/abs/2204.08776)
+
+### Dataset Curators
+
+Divyanshu Aggarwal, Vivek Gupta, Anoop Kunchukuttan
+
+### Licensing Information
+
+Contents of this repository are restricted to only non-commercial research purposes under the [Creative Commons Attribution-NonCommercial 4.0 International License (CC BY-NC 4.0)](https://creativecommons.org/licenses/by-nc/4.0/). Copyright of the dataset contents belongs to the original copyright holders.
+
+### Citation Information
+
+If you use any of the datasets, models or code modules, please cite the following paper:
+
+```
+@misc{https://doi.org/10.48550/arxiv.2204.08776,
+  doi = {10.48550/ARXIV.2204.08776},
+  
+  url = {https://arxiv.org/abs/2204.08776},
+  
+  author = {Aggarwal, Divyanshu and Gupta, Vivek and Kunchukuttan, Anoop},
+  
+  keywords = {Computation and Language (cs.CL), Artificial Intelligence (cs.AI), FOS: Computer and information sciences, FOS: Computer and information sciences},
+  
+  title = {IndicXNLI: Evaluating Multilingual Inference for Indian Languages}, 
+  
+  publisher = {arXiv},
+  
+  year = {2022},
+  
+  copyright = {Creative Commons Attribution 4.0 International}
+}
+```
+
+<!-- ### Contributions -->

.history/README_20230707233537.md

@@ -0,0 +1,234 @@
+---
+annotations_creators:
+- machine-generated
+language_creators:
+- machine-generated
+language:
+- as
+- bn
+- gu
+- hi
+- kn
+- ml
+- mr
+- or
+- pa
+- ta
+- te
+license:
+- cc0-1.0
+multilinguality:
+- multilingual
+pretty_name: IE-SemParse
+size_categories:
+- 1M<n<10M
+source_datasets:
+- original
+task_categories:
+- text-classification
+task_ids:
+- natural-language-inference
+---
+
+# Dataset Card for "IE-SemParse"
+
+## Table of Contents
+
+- [Dataset Card for "IE-SemParse"](#dataset-card-for-ie-semparse)
+  - [Table of Contents](#table-of-contents)
+  - [Dataset Description](#dataset-description)
+    - [Dataset Summary](#dataset-summary)
+    - [Supported Tasks and Leaderboards](#supported-tasks-and-leaderboards)
+    - [Languages](#languages)
+  - [Dataset Structure](#dataset-structure)
+    - [Data Instances](#data-instances)
+    - [Data Fields](#data-fields)
+    - [Data Splits](#data-splits)
+  - [Dataset usage](#dataset-usage)
+  - [Dataset Creation](#dataset-creation)
+    - [Curation Rationale](#curation-rationale)
+    - [Source Data](#source-data)
+      - [Initial Data Collection and Normalization](#initial-data-collection-and-normalization)
+      - [Who are the source language producers?](#who-are-the-source-language-producers)
+      - [Human Verification Process](#human-verification-process)
+  - [Considerations for Using the Data](#considerations-for-using-the-data)
+    - [Social Impact of Dataset](#social-impact-of-dataset)
+    - [Discussion of Biases](#discussion-of-biases)
+    - [Other Known Limitations](#other-known-limitations)
+    - [Dataset Curators](#dataset-curators)
+    - [Licensing Information](#licensing-information)
+    - [Citation Information](#citation-information)
+
+## Dataset Description
+
+- **Homepage:** <https://github.com/divyanshuaggarwal/IE-SemParse>
+- **Paper:** [IE-SemParse: Evaluating Multilingual Inference for Indian Languages](https://arxiv.org/abs/2204.08776)
+- **Point of Contact:** [Divyanshu Aggarwal](mailto:[email protected])
+
+### Dataset Summary
+
+INDICXNLI is similar to existing
+XNLI dataset in shape/form, but focusses on Indic language family. INDICXNLI include NLI
+data for eleven major Indic languages that includes
+Assamese (‘as’), Gujarat (‘gu’), Kannada (‘kn’),
+Malayalam (‘ml’), Marathi (‘mr’), Odia (‘or’),
+Punjabi (‘pa’), Tamil (‘ta’), Telugu (‘te’), Hindi
+(‘hi’), and Bengali (‘bn’).
+
+### Supported Tasks and Leaderboards
+
+**Tasks:** Natural Language Inference
+
+**Leaderboards:** Currently there is no Leaderboard for this dataset.
+
+### Languages
+
+- `Assamese (as)`
+- `Bengali (bn)`
+- `Gujarati (gu)`
+- `Kannada (kn)`
+- `Hindi (hi)`
+- `Malayalam (ml)`
+- `Marathi (mr)`
+- `Oriya (or)`
+- `Punjabi (pa)`
+- `Tamil (ta)`
+- `Telugu (te)`
+
+## Dataset Structure
+
+### Data Instances
+
+One example from the `hi` dataset is given below in JSON format.
+
+  ```python
+ {'premise': 'अवधारणात्मक रूप से क्रीम स्किमिंग के दो बुनियादी आयाम हैं-उत्पाद और भूगोल।',
+ 'hypothesis': 'उत्पाद और भूगोल क्रीम स्किमिंग का काम करते हैं।',
+ 'label': 1 (neutral) }
+  ```
+
+### Data Fields
+
+- `premise (string)`: Premise Sentence
+- `hypothesis (string)`: Hypothesis Sentence
+- `label (integer)`: Integer label `0` if hypothesis `entails` the premise, `2` if hypothesis `negates` the premise and `1` otherwise.
+
+### Data Splits
+
+<!-- Below is the dataset split given for `hi` dataset.
+
+```python
+DatasetDict({
+    train: Dataset({
+        features: ['premise', 'hypothesis', 'label'],
+        num_rows: 392702
+    })
+    test: Dataset({
+        features: ['premise', 'hypothesis', 'label'],
+        num_rows: 5010
+    })
+    validation: Dataset({
+        features: ['premise', 'hypothesis', 'label'],
+        num_rows: 2490
+    })
+})
+
+``` -->
+
+Language      | ISO 639-1 Code |Train | Dev | Test |
+--------------|----------------|-------|-----|------|
+Assamese | as | 392,702 | 5,010 | 2,490 |
+Bengali | bn | 392,702 | 5,010 | 2,490 |
+Gujarati | gu |  392,702 | 5,010 | 2,490 |
+Hindi | hi | 392,702 | 5,010 | 2,490 |
+Kannada | kn |  392,702 | 5,010 | 2,490 |
+Malayalam | ml |392,702  | 5,010 | 2,490 |
+Marathi | mr |392,702 | 5,010 | 2,490 |
+Oriya | or | 392,702 | 5,010 | 2,490 |
+Punjabi | pa | 392,702 | 5,010 | 2,490 |
+Tamil | ta | 392,702 | 5,010 | 2,490 |
+Telugu | te | 392,702 | 5,010 | 2,490 |
+
+<!-- The dataset split remains same across all languages. -->
+
+## Dataset usage
+
+Code snippet for using the dataset using datasets library.
+
+```python
+from datasets import load_dataset
+
+dataset = load_dataset("Divyanshu/indicxnli")
+```
+
+## Dataset Creation
+
+Machine translation of XNLI english dataset to 11 listed Indic Languages.
+
+### Curation Rationale
+
+[More information needed]
+
+### Source Data
+
+[XNLI dataset](https://cims.nyu.edu/~sbowman/xnli/)
+
+#### Initial Data Collection and Normalization
+
+[Detailed in the paper](https://arxiv.org/abs/2204.08776)
+
+#### Who are the source language producers?
+
+[Detailed in the paper](https://arxiv.org/abs/2204.08776)
+
+#### Human Verification Process
+
+[Detailed in the paper](https://arxiv.org/abs/2204.08776)
+
+## Considerations for Using the Data
+
+### Social Impact of Dataset
+
+[Detailed in the paper](https://arxiv.org/abs/2204.08776)
+
+### Discussion of Biases
+
+[Detailed in the paper](https://arxiv.org/abs/2204.08776)
+
+### Other Known Limitations
+
+[Detailed in the paper](https://arxiv.org/abs/2204.08776)
+
+### Dataset Curators
+
+Divyanshu Aggarwal, Vivek Gupta, Anoop Kunchukuttan
+
+### Licensing Information
+
+Contents of this repository are restricted to only non-commercial research purposes under the [Creative Commons Attribution-NonCommercial 4.0 International License (CC BY-NC 4.0)](https://creativecommons.org/licenses/by-nc/4.0/). Copyright of the dataset contents belongs to the original copyright holders.
+
+### Citation Information
+
+If you use any of the datasets, models or code modules, please cite the following paper:
+
+```
+@misc{https://doi.org/10.48550/arxiv.2204.08776,
+  doi = {10.48550/ARXIV.2204.08776},
+  
+  url = {https://arxiv.org/abs/2204.08776},
+  
+  author = {Aggarwal, Divyanshu and Gupta, Vivek and Kunchukuttan, Anoop},
+  
+  keywords = {Computation and Language (cs.CL), Artificial Intelligence (cs.AI), FOS: Computer and information sciences, FOS: Computer and information sciences},
+  
+  title = {IE-SemParse: Evaluating Multilingual Inference for Indian Languages}, 
+  
+  publisher = {arXiv},
+  
+  year = {2022},
+  
+  copyright = {Creative Commons Attribution 4.0 International}
+}
+```
+
+<!-- ### Contributions -->

.history/README_20230707233553.md

@@ -0,0 +1,234 @@
+---
+annotations_creators:
+- machine-generated
+language_creators:
+- machine-generated
+language:
+- as
+- bn
+- gu
+- hi
+- kn
+- ml
+- mr
+- or
+- pa
+- ta
+- te
+license:
+- cc0-1.0
+multilinguality:
+- multilingual
+pretty_name: IE-SemParse
+size_categories:
+- 1M<n<10M
+source_datasets:
+- original
+task_categories:
+- text-classification
+task_ids:
+- Sema
+---
+
+# Dataset Card for "IE-SemParse"
+
+## Table of Contents
+
+- [Dataset Card for "IE-SemParse"](#dataset-card-for-ie-semparse)
+  - [Table of Contents](#table-of-contents)
+  - [Dataset Description](#dataset-description)
+    - [Dataset Summary](#dataset-summary)
+    - [Supported Tasks and Leaderboards](#supported-tasks-and-leaderboards)
+    - [Languages](#languages)
+  - [Dataset Structure](#dataset-structure)
+    - [Data Instances](#data-instances)
+    - [Data Fields](#data-fields)
+    - [Data Splits](#data-splits)
+  - [Dataset usage](#dataset-usage)
+  - [Dataset Creation](#dataset-creation)
+    - [Curation Rationale](#curation-rationale)
+    - [Source Data](#source-data)
+      - [Initial Data Collection and Normalization](#initial-data-collection-and-normalization)
+      - [Who are the source language producers?](#who-are-the-source-language-producers)
+      - [Human Verification Process](#human-verification-process)
+  - [Considerations for Using the Data](#considerations-for-using-the-data)
+    - [Social Impact of Dataset](#social-impact-of-dataset)
+    - [Discussion of Biases](#discussion-of-biases)
+    - [Other Known Limitations](#other-known-limitations)
+    - [Dataset Curators](#dataset-curators)
+    - [Licensing Information](#licensing-information)
+    - [Citation Information](#citation-information)
+
+## Dataset Description
+
+- **Homepage:** <https://github.com/divyanshuaggarwal/IE-SemParse>
+- **Paper:** [IE-SemParse: Evaluating Multilingual Inference for Indian Languages](https://arxiv.org/abs/2204.08776)
+- **Point of Contact:** [Divyanshu Aggarwal](mailto:[email protected])
+
+### Dataset Summary
+
+INDICXNLI is similar to existing
+XNLI dataset in shape/form, but focusses on Indic language family. INDICXNLI include NLI
+data for eleven major Indic languages that includes
+Assamese (‘as’), Gujarat (‘gu’), Kannada (‘kn’),
+Malayalam (‘ml’), Marathi (‘mr’), Odia (‘or’),
+Punjabi (‘pa’), Tamil (‘ta’), Telugu (‘te’), Hindi
+(‘hi’), and Bengali (‘bn’).
+
+### Supported Tasks and Leaderboards
+
+**Tasks:** Natural Language Inference
+
+**Leaderboards:** Currently there is no Leaderboard for this dataset.
+
+### Languages
+
+- `Assamese (as)`
+- `Bengali (bn)`
+- `Gujarati (gu)`
+- `Kannada (kn)`
+- `Hindi (hi)`
+- `Malayalam (ml)`
+- `Marathi (mr)`
+- `Oriya (or)`
+- `Punjabi (pa)`
+- `Tamil (ta)`
+- `Telugu (te)`
+
+## Dataset Structure
+
+### Data Instances
+
+One example from the `hi` dataset is given below in JSON format.
+
+  ```python
+ {'premise': 'अवधारणात्मक रूप से क्रीम स्किमिंग के दो बुनियादी आयाम हैं-उत्पाद और भूगोल।',
+ 'hypothesis': 'उत्पाद और भूगोल क्रीम स्किमिंग का काम करते हैं।',
+ 'label': 1 (neutral) }
+  ```
+
+### Data Fields
+
+- `premise (string)`: Premise Sentence
+- `hypothesis (string)`: Hypothesis Sentence
+- `label (integer)`: Integer label `0` if hypothesis `entails` the premise, `2` if hypothesis `negates` the premise and `1` otherwise.
+
+### Data Splits
+
+<!-- Below is the dataset split given for `hi` dataset.
+
+```python
+DatasetDict({
+    train: Dataset({
+        features: ['premise', 'hypothesis', 'label'],
+        num_rows: 392702
+    })
+    test: Dataset({
+        features: ['premise', 'hypothesis', 'label'],
+        num_rows: 5010
+    })
+    validation: Dataset({
+        features: ['premise', 'hypothesis', 'label'],
+        num_rows: 2490
+    })
+})
+
+``` -->
+
+Language      | ISO 639-1 Code |Train | Dev | Test |
+--------------|----------------|-------|-----|------|
+Assamese | as | 392,702 | 5,010 | 2,490 |
+Bengali | bn | 392,702 | 5,010 | 2,490 |
+Gujarati | gu |  392,702 | 5,010 | 2,490 |
+Hindi | hi | 392,702 | 5,010 | 2,490 |
+Kannada | kn |  392,702 | 5,010 | 2,490 |
+Malayalam | ml |392,702  | 5,010 | 2,490 |
+Marathi | mr |392,702 | 5,010 | 2,490 |
+Oriya | or | 392,702 | 5,010 | 2,490 |
+Punjabi | pa | 392,702 | 5,010 | 2,490 |
+Tamil | ta | 392,702 | 5,010 | 2,490 |
+Telugu | te | 392,702 | 5,010 | 2,490 |
+
+<!-- The dataset split remains same across all languages. -->
+
+## Dataset usage
+
+Code snippet for using the dataset using datasets library.
+
+```python
+from datasets import load_dataset
+
+dataset = load_dataset("Divyanshu/indicxnli")
+```
+
+## Dataset Creation
+
+Machine translation of XNLI english dataset to 11 listed Indic Languages.
+
+### Curation Rationale
+
+[More information needed]
+
+### Source Data
+
+[XNLI dataset](https://cims.nyu.edu/~sbowman/xnli/)
+
+#### Initial Data Collection and Normalization
+
+[Detailed in the paper](https://arxiv.org/abs/2204.08776)
+
+#### Who are the source language producers?
+
+[Detailed in the paper](https://arxiv.org/abs/2204.08776)
+
+#### Human Verification Process
+
+[Detailed in the paper](https://arxiv.org/abs/2204.08776)
+
+## Considerations for Using the Data
+
+### Social Impact of Dataset
+
+[Detailed in the paper](https://arxiv.org/abs/2204.08776)
+
+### Discussion of Biases
+
+[Detailed in the paper](https://arxiv.org/abs/2204.08776)
+
+### Other Known Limitations
+
+[Detailed in the paper](https://arxiv.org/abs/2204.08776)
+
+### Dataset Curators
+
+Divyanshu Aggarwal, Vivek Gupta, Anoop Kunchukuttan
+
+### Licensing Information
+
+Contents of this repository are restricted to only non-commercial research purposes under the [Creative Commons Attribution-NonCommercial 4.0 International License (CC BY-NC 4.0)](https://creativecommons.org/licenses/by-nc/4.0/). Copyright of the dataset contents belongs to the original copyright holders.
+
+### Citation Information
+
+If you use any of the datasets, models or code modules, please cite the following paper:
+
+```
+@misc{https://doi.org/10.48550/arxiv.2204.08776,
+  doi = {10.48550/ARXIV.2204.08776},
+  
+  url = {https://arxiv.org/abs/2204.08776},
+  
+  author = {Aggarwal, Divyanshu and Gupta, Vivek and Kunchukuttan, Anoop},
+  
+  keywords = {Computation and Language (cs.CL), Artificial Intelligence (cs.AI), FOS: Computer and information sciences, FOS: Computer and information sciences},
+  
+  title = {IE-SemParse: Evaluating Multilingual Inference for Indian Languages}, 
+  
+  publisher = {arXiv},
+  
+  year = {2022},
+  
+  copyright = {Creative Commons Attribution 4.0 International}
+}
+```
+
+<!-- ### Contributions -->

.history/README_20230707233556.md

@@ -0,0 +1,234 @@
+---
+annotations_creators:
+- machine-generated
+language_creators:
+- machine-generated
+language:
+- as
+- bn
+- gu
+- hi
+- kn
+- ml
+- mr
+- or
+- pa
+- ta
+- te
+license:
+- cc0-1.0
+multilinguality:
+- multilingual
+pretty_name: IE-SemParse
+size_categories:
+- 1M<n<10M
+source_datasets:
+- original
+task_categories:
+- text-classification
+task_ids:
+- Semantic
+---
+
+# Dataset Card for "IE-SemParse"
+
+## Table of Contents
+
+- [Dataset Card for "IE-SemParse"](#dataset-card-for-ie-semparse)
+  - [Table of Contents](#table-of-contents)
+  - [Dataset Description](#dataset-description)
+    - [Dataset Summary](#dataset-summary)
+    - [Supported Tasks and Leaderboards](#supported-tasks-and-leaderboards)
+    - [Languages](#languages)
+  - [Dataset Structure](#dataset-structure)
+    - [Data Instances](#data-instances)
+    - [Data Fields](#data-fields)
+    - [Data Splits](#data-splits)
+  - [Dataset usage](#dataset-usage)
+  - [Dataset Creation](#dataset-creation)
+    - [Curation Rationale](#curation-rationale)
+    - [Source Data](#source-data)
+      - [Initial Data Collection and Normalization](#initial-data-collection-and-normalization)
+      - [Who are the source language producers?](#who-are-the-source-language-producers)
+      - [Human Verification Process](#human-verification-process)
+  - [Considerations for Using the Data](#considerations-for-using-the-data)
+    - [Social Impact of Dataset](#social-impact-of-dataset)
+    - [Discussion of Biases](#discussion-of-biases)
+    - [Other Known Limitations](#other-known-limitations)
+    - [Dataset Curators](#dataset-curators)
+    - [Licensing Information](#licensing-information)
+    - [Citation Information](#citation-information)
+
+## Dataset Description
+
+- **Homepage:** <https://github.com/divyanshuaggarwal/IE-SemParse>
+- **Paper:** [IE-SemParse: Evaluating Multilingual Inference for Indian Languages](https://arxiv.org/abs/2204.08776)
+- **Point of Contact:** [Divyanshu Aggarwal](mailto:[email protected])
+
+### Dataset Summary
+
+INDICXNLI is similar to existing
+XNLI dataset in shape/form, but focusses on Indic language family. INDICXNLI include NLI
+data for eleven major Indic languages that includes
+Assamese (‘as’), Gujarat (‘gu’), Kannada (‘kn’),
+Malayalam (‘ml’), Marathi (‘mr’), Odia (‘or’),
+Punjabi (‘pa’), Tamil (‘ta’), Telugu (‘te’), Hindi
+(‘hi’), and Bengali (‘bn’).
+
+### Supported Tasks and Leaderboards
+
+**Tasks:** Natural Language Inference
+
+**Leaderboards:** Currently there is no Leaderboard for this dataset.
+
+### Languages
+
+- `Assamese (as)`
+- `Bengali (bn)`
+- `Gujarati (gu)`
+- `Kannada (kn)`
+- `Hindi (hi)`
+- `Malayalam (ml)`
+- `Marathi (mr)`
+- `Oriya (or)`
+- `Punjabi (pa)`
+- `Tamil (ta)`
+- `Telugu (te)`
+
+## Dataset Structure
+
+### Data Instances
+
+One example from the `hi` dataset is given below in JSON format.
+
+  ```python
+ {'premise': 'अवधारणात्मक रूप से क्रीम स्किमिंग के दो बुनियादी आयाम हैं-उत्पाद और भूगोल।',
+ 'hypothesis': 'उत्पाद और भूगोल क्रीम स्किमिंग का काम करते हैं।',
+ 'label': 1 (neutral) }
+  ```
+
+### Data Fields
+
+- `premise (string)`: Premise Sentence
+- `hypothesis (string)`: Hypothesis Sentence
+- `label (integer)`: Integer label `0` if hypothesis `entails` the premise, `2` if hypothesis `negates` the premise and `1` otherwise.
+
+### Data Splits
+
+<!-- Below is the dataset split given for `hi` dataset.
+
+```python
+DatasetDict({
+    train: Dataset({
+        features: ['premise', 'hypothesis', 'label'],
+        num_rows: 392702
+    })
+    test: Dataset({
+        features: ['premise', 'hypothesis', 'label'],
+        num_rows: 5010
+    })
+    validation: Dataset({
+        features: ['premise', 'hypothesis', 'label'],
+        num_rows: 2490
+    })
+})
+
+``` -->
+
+Language      | ISO 639-1 Code |Train | Dev | Test |
+--------------|----------------|-------|-----|------|
+Assamese | as | 392,702 | 5,010 | 2,490 |
+Bengali | bn | 392,702 | 5,010 | 2,490 |
+Gujarati | gu |  392,702 | 5,010 | 2,490 |
+Hindi | hi | 392,702 | 5,010 | 2,490 |
+Kannada | kn |  392,702 | 5,010 | 2,490 |
+Malayalam | ml |392,702  | 5,010 | 2,490 |
+Marathi | mr |392,702 | 5,010 | 2,490 |
+Oriya | or | 392,702 | 5,010 | 2,490 |
+Punjabi | pa | 392,702 | 5,010 | 2,490 |
+Tamil | ta | 392,702 | 5,010 | 2,490 |
+Telugu | te | 392,702 | 5,010 | 2,490 |
+
+<!-- The dataset split remains same across all languages. -->
+
+## Dataset usage
+
+Code snippet for using the dataset using datasets library.
+
+```python
+from datasets import load_dataset
+
+dataset = load_dataset("Divyanshu/indicxnli")
+```
+
+## Dataset Creation
+
+Machine translation of XNLI english dataset to 11 listed Indic Languages.
+
+### Curation Rationale
+
+[More information needed]
+
+### Source Data
+
+[XNLI dataset](https://cims.nyu.edu/~sbowman/xnli/)
+
+#### Initial Data Collection and Normalization
+
+[Detailed in the paper](https://arxiv.org/abs/2204.08776)
+
+#### Who are the source language producers?
+
+[Detailed in the paper](https://arxiv.org/abs/2204.08776)
+
+#### Human Verification Process
+
+[Detailed in the paper](https://arxiv.org/abs/2204.08776)
+
+## Considerations for Using the Data
+
+### Social Impact of Dataset
+
+[Detailed in the paper](https://arxiv.org/abs/2204.08776)
+
+### Discussion of Biases
+
+[Detailed in the paper](https://arxiv.org/abs/2204.08776)
+
+### Other Known Limitations
+
+[Detailed in the paper](https://arxiv.org/abs/2204.08776)
+
+### Dataset Curators
+
+Divyanshu Aggarwal, Vivek Gupta, Anoop Kunchukuttan
+
+### Licensing Information
+
+Contents of this repository are restricted to only non-commercial research purposes under the [Creative Commons Attribution-NonCommercial 4.0 International License (CC BY-NC 4.0)](https://creativecommons.org/licenses/by-nc/4.0/). Copyright of the dataset contents belongs to the original copyright holders.
+
+### Citation Information
+
+If you use any of the datasets, models or code modules, please cite the following paper:
+
+```
+@misc{https://doi.org/10.48550/arxiv.2204.08776,
+  doi = {10.48550/ARXIV.2204.08776},
+  
+  url = {https://arxiv.org/abs/2204.08776},
+  
+  author = {Aggarwal, Divyanshu and Gupta, Vivek and Kunchukuttan, Anoop},
+  
+  keywords = {Computation and Language (cs.CL), Artificial Intelligence (cs.AI), FOS: Computer and information sciences, FOS: Computer and information sciences},
+  
+  title = {IE-SemParse: Evaluating Multilingual Inference for Indian Languages}, 
+  
+  publisher = {arXiv},
+  
+  year = {2022},
+  
+  copyright = {Creative Commons Attribution 4.0 International}
+}
+```
+
+<!-- ### Contributions -->

.history/README_20230707233559.md

@@ -0,0 +1,234 @@
+---
+annotations_creators:
+- machine-generated
+language_creators:
+- machine-generated
+language:
+- as
+- bn
+- gu
+- hi
+- kn
+- ml
+- mr
+- or
+- pa
+- ta
+- te
+license:
+- cc0-1.0
+multilinguality:
+- multilingual
+pretty_name: IE-SemParse
+size_categories:
+- 1M<n<10M
+source_datasets:
+- original
+task_categories:
+- text-classification
+task_ids:
+- Semantic-Parsing
+---
+
+# Dataset Card for "IE-SemParse"
+
+## Table of Contents
+
+- [Dataset Card for "IE-SemParse"](#dataset-card-for-ie-semparse)
+  - [Table of Contents](#table-of-contents)
+  - [Dataset Description](#dataset-description)
+    - [Dataset Summary](#dataset-summary)
+    - [Supported Tasks and Leaderboards](#supported-tasks-and-leaderboards)
+    - [Languages](#languages)
+  - [Dataset Structure](#dataset-structure)
+    - [Data Instances](#data-instances)
+    - [Data Fields](#data-fields)
+    - [Data Splits](#data-splits)
+  - [Dataset usage](#dataset-usage)
+  - [Dataset Creation](#dataset-creation)
+    - [Curation Rationale](#curation-rationale)
+    - [Source Data](#source-data)
+      - [Initial Data Collection and Normalization](#initial-data-collection-and-normalization)
+      - [Who are the source language producers?](#who-are-the-source-language-producers)
+      - [Human Verification Process](#human-verification-process)
+  - [Considerations for Using the Data](#considerations-for-using-the-data)
+    - [Social Impact of Dataset](#social-impact-of-dataset)
+    - [Discussion of Biases](#discussion-of-biases)
+    - [Other Known Limitations](#other-known-limitations)
+    - [Dataset Curators](#dataset-curators)
+    - [Licensing Information](#licensing-information)
+    - [Citation Information](#citation-information)
+
+## Dataset Description
+
+- **Homepage:** <https://github.com/divyanshuaggarwal/IE-SemParse>
+- **Paper:** [IE-SemParse: Evaluating Multilingual Inference for Indian Languages](https://arxiv.org/abs/2204.08776)
+- **Point of Contact:** [Divyanshu Aggarwal](mailto:[email protected])
+
+### Dataset Summary
+
+INDICXNLI is similar to existing
+XNLI dataset in shape/form, but focusses on Indic language family. INDICXNLI include NLI
+data for eleven major Indic languages that includes
+Assamese (‘as’), Gujarat (‘gu’), Kannada (‘kn’),
+Malayalam (‘ml’), Marathi (‘mr’), Odia (‘or’),
+Punjabi (‘pa’), Tamil (‘ta’), Telugu (‘te’), Hindi
+(‘hi’), and Bengali (‘bn’).
+
+### Supported Tasks and Leaderboards
+
+**Tasks:** Natural Language Inference
+
+**Leaderboards:** Currently there is no Leaderboard for this dataset.
+
+### Languages
+
+- `Assamese (as)`
+- `Bengali (bn)`
+- `Gujarati (gu)`
+- `Kannada (kn)`
+- `Hindi (hi)`
+- `Malayalam (ml)`
+- `Marathi (mr)`
+- `Oriya (or)`
+- `Punjabi (pa)`
+- `Tamil (ta)`
+- `Telugu (te)`
+
+## Dataset Structure
+
+### Data Instances
+
+One example from the `hi` dataset is given below in JSON format.
+
+  ```python
+ {'premise': 'अवधारणात्मक रूप से क्रीम स्किमिंग के दो बुनियादी आयाम हैं-उत्पाद और भूगोल।',
+ 'hypothesis': 'उत्पाद और भूगोल क्रीम स्किमिंग का काम करते हैं।',
+ 'label': 1 (neutral) }
+  ```
+
+### Data Fields
+
+- `premise (string)`: Premise Sentence
+- `hypothesis (string)`: Hypothesis Sentence
+- `label (integer)`: Integer label `0` if hypothesis `entails` the premise, `2` if hypothesis `negates` the premise and `1` otherwise.
+
+### Data Splits
+
+<!-- Below is the dataset split given for `hi` dataset.
+
+```python
+DatasetDict({
+    train: Dataset({
+        features: ['premise', 'hypothesis', 'label'],
+        num_rows: 392702
+    })
+    test: Dataset({
+        features: ['premise', 'hypothesis', 'label'],
+        num_rows: 5010
+    })
+    validation: Dataset({
+        features: ['premise', 'hypothesis', 'label'],
+        num_rows: 2490
+    })
+})
+
+``` -->
+
+Language      | ISO 639-1 Code |Train | Dev | Test |
+--------------|----------------|-------|-----|------|
+Assamese | as | 392,702 | 5,010 | 2,490 |
+Bengali | bn | 392,702 | 5,010 | 2,490 |
+Gujarati | gu |  392,702 | 5,010 | 2,490 |
+Hindi | hi | 392,702 | 5,010 | 2,490 |
+Kannada | kn |  392,702 | 5,010 | 2,490 |
+Malayalam | ml |392,702  | 5,010 | 2,490 |
+Marathi | mr |392,702 | 5,010 | 2,490 |
+Oriya | or | 392,702 | 5,010 | 2,490 |
+Punjabi | pa | 392,702 | 5,010 | 2,490 |
+Tamil | ta | 392,702 | 5,010 | 2,490 |
+Telugu | te | 392,702 | 5,010 | 2,490 |
+
+<!-- The dataset split remains same across all languages. -->
+
+## Dataset usage
+
+Code snippet for using the dataset using datasets library.
+
+```python
+from datasets import load_dataset
+
+dataset = load_dataset("Divyanshu/indicxnli")
+```
+
+## Dataset Creation
+
+Machine translation of XNLI english dataset to 11 listed Indic Languages.
+
+### Curation Rationale
+
+[More information needed]
+
+### Source Data
+
+[XNLI dataset](https://cims.nyu.edu/~sbowman/xnli/)
+
+#### Initial Data Collection and Normalization
+
+[Detailed in the paper](https://arxiv.org/abs/2204.08776)
+
+#### Who are the source language producers?
+
+[Detailed in the paper](https://arxiv.org/abs/2204.08776)
+
+#### Human Verification Process
+
+[Detailed in the paper](https://arxiv.org/abs/2204.08776)
+
+## Considerations for Using the Data
+
+### Social Impact of Dataset
+
+[Detailed in the paper](https://arxiv.org/abs/2204.08776)
+
+### Discussion of Biases
+
+[Detailed in the paper](https://arxiv.org/abs/2204.08776)
+
+### Other Known Limitations
+
+[Detailed in the paper](https://arxiv.org/abs/2204.08776)
+
+### Dataset Curators
+
+Divyanshu Aggarwal, Vivek Gupta, Anoop Kunchukuttan
+
+### Licensing Information
+
+Contents of this repository are restricted to only non-commercial research purposes under the [Creative Commons Attribution-NonCommercial 4.0 International License (CC BY-NC 4.0)](https://creativecommons.org/licenses/by-nc/4.0/). Copyright of the dataset contents belongs to the original copyright holders.
+
+### Citation Information
+
+If you use any of the datasets, models or code modules, please cite the following paper:
+
+```
+@misc{https://doi.org/10.48550/arxiv.2204.08776,
+  doi = {10.48550/ARXIV.2204.08776},
+  
+  url = {https://arxiv.org/abs/2204.08776},
+  
+  author = {Aggarwal, Divyanshu and Gupta, Vivek and Kunchukuttan, Anoop},
+  
+  keywords = {Computation and Language (cs.CL), Artificial Intelligence (cs.AI), FOS: Computer and information sciences, FOS: Computer and information sciences},
+  
+  title = {IE-SemParse: Evaluating Multilingual Inference for Indian Languages}, 
+  
+  publisher = {arXiv},
+  
+  year = {2022},
+  
+  copyright = {Creative Commons Attribution 4.0 International}
+}
+```
+
+<!-- ### Contributions -->

.history/README_20230707233606.md

@@ -0,0 +1,234 @@
+---
+annotations_creators:
+- machine-generated
+language_creators:
+- machine-generated
+language:
+- as
+- bn
+- gu
+- hi
+- kn
+- ml
+- mr
+- or
+- pa
+- ta
+- te
+license:
+- cc0-1.0
+multilinguality:
+- multilingual
+pretty_name: IE-SemParse
+size_categories:
+- 1M<n<10M
+source_datasets:
+- original
+task_categories:
+- text2text
+task_ids:
+- Semantic-Parsing
+---
+
+# Dataset Card for "IE-SemParse"
+
+## Table of Contents
+
+- [Dataset Card for "IE-SemParse"](#dataset-card-for-ie-semparse)
+  - [Table of Contents](#table-of-contents)
+  - [Dataset Description](#dataset-description)
+    - [Dataset Summary](#dataset-summary)
+    - [Supported Tasks and Leaderboards](#supported-tasks-and-leaderboards)
+    - [Languages](#languages)
+  - [Dataset Structure](#dataset-structure)
+    - [Data Instances](#data-instances)
+    - [Data Fields](#data-fields)
+    - [Data Splits](#data-splits)
+  - [Dataset usage](#dataset-usage)
+  - [Dataset Creation](#dataset-creation)
+    - [Curation Rationale](#curation-rationale)
+    - [Source Data](#source-data)
+      - [Initial Data Collection and Normalization](#initial-data-collection-and-normalization)
+      - [Who are the source language producers?](#who-are-the-source-language-producers)
+      - [Human Verification Process](#human-verification-process)
+  - [Considerations for Using the Data](#considerations-for-using-the-data)
+    - [Social Impact of Dataset](#social-impact-of-dataset)
+    - [Discussion of Biases](#discussion-of-biases)
+    - [Other Known Limitations](#other-known-limitations)
+    - [Dataset Curators](#dataset-curators)
+    - [Licensing Information](#licensing-information)
+    - [Citation Information](#citation-information)
+
+## Dataset Description
+
+- **Homepage:** <https://github.com/divyanshuaggarwal/IE-SemParse>
+- **Paper:** [IE-SemParse: Evaluating Multilingual Inference for Indian Languages](https://arxiv.org/abs/2204.08776)
+- **Point of Contact:** [Divyanshu Aggarwal](mailto:[email protected])
+
+### Dataset Summary
+
+INDICXNLI is similar to existing
+XNLI dataset in shape/form, but focusses on Indic language family. INDICXNLI include NLI
+data for eleven major Indic languages that includes
+Assamese (‘as’), Gujarat (‘gu’), Kannada (‘kn’),
+Malayalam (‘ml’), Marathi (‘mr’), Odia (‘or’),
+Punjabi (‘pa’), Tamil (‘ta’), Telugu (‘te’), Hindi
+(‘hi’), and Bengali (‘bn’).
+
+### Supported Tasks and Leaderboards
+
+**Tasks:** Natural Language Inference
+
+**Leaderboards:** Currently there is no Leaderboard for this dataset.
+
+### Languages
+
+- `Assamese (as)`
+- `Bengali (bn)`
+- `Gujarati (gu)`
+- `Kannada (kn)`
+- `Hindi (hi)`
+- `Malayalam (ml)`
+- `Marathi (mr)`
+- `Oriya (or)`
+- `Punjabi (pa)`
+- `Tamil (ta)`
+- `Telugu (te)`
+
+## Dataset Structure
+
+### Data Instances
+
+One example from the `hi` dataset is given below in JSON format.
+
+  ```python
+ {'premise': 'अवधारणात्मक रूप से क्रीम स्किमिंग के दो बुनियादी आयाम हैं-उत्पाद और भूगोल।',
+ 'hypothesis': 'उत्पाद और भूगोल क्रीम स्किमिंग का काम करते हैं।',
+ 'label': 1 (neutral) }
+  ```
+
+### Data Fields
+
+- `premise (string)`: Premise Sentence
+- `hypothesis (string)`: Hypothesis Sentence
+- `label (integer)`: Integer label `0` if hypothesis `entails` the premise, `2` if hypothesis `negates` the premise and `1` otherwise.
+
+### Data Splits
+
+<!-- Below is the dataset split given for `hi` dataset.
+
+```python
+DatasetDict({
+    train: Dataset({
+        features: ['premise', 'hypothesis', 'label'],
+        num_rows: 392702
+    })
+    test: Dataset({
+        features: ['premise', 'hypothesis', 'label'],
+        num_rows: 5010
+    })
+    validation: Dataset({
+        features: ['premise', 'hypothesis', 'label'],
+        num_rows: 2490
+    })
+})
+
+``` -->
+
+Language      | ISO 639-1 Code |Train | Dev | Test |
+--------------|----------------|-------|-----|------|
+Assamese | as | 392,702 | 5,010 | 2,490 |
+Bengali | bn | 392,702 | 5,010 | 2,490 |
+Gujarati | gu |  392,702 | 5,010 | 2,490 |
+Hindi | hi | 392,702 | 5,010 | 2,490 |
+Kannada | kn |  392,702 | 5,010 | 2,490 |
+Malayalam | ml |392,702  | 5,010 | 2,490 |
+Marathi | mr |392,702 | 5,010 | 2,490 |
+Oriya | or | 392,702 | 5,010 | 2,490 |
+Punjabi | pa | 392,702 | 5,010 | 2,490 |
+Tamil | ta | 392,702 | 5,010 | 2,490 |
+Telugu | te | 392,702 | 5,010 | 2,490 |
+
+<!-- The dataset split remains same across all languages. -->
+
+## Dataset usage
+
+Code snippet for using the dataset using datasets library.
+
+```python
+from datasets import load_dataset
+
+dataset = load_dataset("Divyanshu/indicxnli")
+```
+
+## Dataset Creation
+
+Machine translation of XNLI english dataset to 11 listed Indic Languages.
+
+### Curation Rationale
+
+[More information needed]
+
+### Source Data
+
+[XNLI dataset](https://cims.nyu.edu/~sbowman/xnli/)
+
+#### Initial Data Collection and Normalization
+
+[Detailed in the paper](https://arxiv.org/abs/2204.08776)
+
+#### Who are the source language producers?
+
+[Detailed in the paper](https://arxiv.org/abs/2204.08776)
+
+#### Human Verification Process
+
+[Detailed in the paper](https://arxiv.org/abs/2204.08776)
+
+## Considerations for Using the Data
+
+### Social Impact of Dataset
+
+[Detailed in the paper](https://arxiv.org/abs/2204.08776)
+
+### Discussion of Biases
+
+[Detailed in the paper](https://arxiv.org/abs/2204.08776)
+
+### Other Known Limitations
+
+[Detailed in the paper](https://arxiv.org/abs/2204.08776)
+
+### Dataset Curators
+
+Divyanshu Aggarwal, Vivek Gupta, Anoop Kunchukuttan
+
+### Licensing Information
+
+Contents of this repository are restricted to only non-commercial research purposes under the [Creative Commons Attribution-NonCommercial 4.0 International License (CC BY-NC 4.0)](https://creativecommons.org/licenses/by-nc/4.0/). Copyright of the dataset contents belongs to the original copyright holders.
+
+### Citation Information
+
+If you use any of the datasets, models or code modules, please cite the following paper:
+
+```
+@misc{https://doi.org/10.48550/arxiv.2204.08776,
+  doi = {10.48550/ARXIV.2204.08776},
+  
+  url = {https://arxiv.org/abs/2204.08776},
+  
+  author = {Aggarwal, Divyanshu and Gupta, Vivek and Kunchukuttan, Anoop},
+  
+  keywords = {Computation and Language (cs.CL), Artificial Intelligence (cs.AI), FOS: Computer and information sciences, FOS: Computer and information sciences},
+  
+  title = {IE-SemParse: Evaluating Multilingual Inference for Indian Languages}, 
+  
+  publisher = {arXiv},
+  
+  year = {2022},
+  
+  copyright = {Creative Commons Attribution 4.0 International}
+}
+```
+
+<!-- ### Contributions -->

.history/README_20230707233630.md

@@ -0,0 +1,234 @@
+---
+annotations_creators:
+- machine-generated
+language_creators:
+- machine-generated
+language:
+- as
+- bn
+- gu
+- hi
+- kn
+- ml
+- mr
+- or
+- pa
+- ta
+- te
+license:
+- cc0-1.0
+multilinguality:
+- multilingual
+pretty_name: IE-SemParse
+size_categories:
+- 1M<n<10M
+source_datasets:
+- original
+task_categories:
+- text2text
+task_ids:
+- Semantic-Parsing
+---
+
+# Dataset Card for "IE-SemParse"
+
+## Table of Contents
+
+- [Dataset Card for "IE-SemParse"](#dataset-card-for-ie-semparse)
+  - [Table of Contents](#table-of-contents)
+  - [Dataset Description](#dataset-description)
+    - [Dataset Summary](#dataset-summary)
+    - [Supported Tasks and Leaderboards](#supported-tasks-and-leaderboards)
+    - [Languages](#languages)
+  - [Dataset Structure](#dataset-structure)
+    - [Data Instances](#data-instances)
+    - [Data Fields](#data-fields)
+    - [Data Splits](#data-splits)
+  - [Dataset usage](#dataset-usage)
+  - [Dataset Creation](#dataset-creation)
+    - [Curation Rationale](#curation-rationale)
+    - [Source Data](#source-data)
+      - [Initial Data Collection and Normalization](#initial-data-collection-and-normalization)
+      - [Who are the source language producers?](#who-are-the-source-language-producers)
+      - [Human Verification Process](#human-verification-process)
+  - [Considerations for Using the Data](#considerations-for-using-the-data)
+    - [Social Impact of Dataset](#social-impact-of-dataset)
+    - [Discussion of Biases](#discussion-of-biases)
+    - [Other Known Limitations](#other-known-limitations)
+    - [Dataset Curators](#dataset-curators)
+    - [Licensing Information](#licensing-information)
+    - [Citation Information](#citation-information)
+
+## Dataset Description
+
+- **Homepage:** <https://github.com/divyanshuaggarwal/IE-SemParse>
+- **Paper:** [Evaluating Inter-Bilingual Semantic Parsing for Indian Languages](https://arxiv.org/abs/2204.08776)
+- **Point of Contact:** [Divyanshu Aggarwal](mailto:[email protected])
+
+### Dataset Summary
+
+INDICXNLI is similar to existing
+XNLI dataset in shape/form, but focusses on Indic language family. INDICXNLI include NLI
+data for eleven major Indic languages that includes
+Assamese (‘as’), Gujarat (‘gu’), Kannada (‘kn’),
+Malayalam (‘ml’), Marathi (‘mr’), Odia (‘or’),
+Punjabi (‘pa’), Tamil (‘ta’), Telugu (‘te’), Hindi
+(‘hi’), and Bengali (‘bn’).
+
+### Supported Tasks and Leaderboards
+
+**Tasks:** Natural Language Inference
+
+**Leaderboards:** Currently there is no Leaderboard for this dataset.
+
+### Languages
+
+- `Assamese (as)`
+- `Bengali (bn)`
+- `Gujarati (gu)`
+- `Kannada (kn)`
+- `Hindi (hi)`
+- `Malayalam (ml)`
+- `Marathi (mr)`
+- `Oriya (or)`
+- `Punjabi (pa)`
+- `Tamil (ta)`
+- `Telugu (te)`
+
+## Dataset Structure
+
+### Data Instances
+
+One example from the `hi` dataset is given below in JSON format.
+
+  ```python
+ {'premise': 'अवधारणात्मक रूप से क्रीम स्किमिंग के दो बुनियादी आयाम हैं-उत्पाद और भूगोल।',
+ 'hypothesis': 'उत्पाद और भूगोल क्रीम स्किमिंग का काम करते हैं।',
+ 'label': 1 (neutral) }
+  ```
+
+### Data Fields
+
+- `premise (string)`: Premise Sentence
+- `hypothesis (string)`: Hypothesis Sentence
+- `label (integer)`: Integer label `0` if hypothesis `entails` the premise, `2` if hypothesis `negates` the premise and `1` otherwise.
+
+### Data Splits
+
+<!-- Below is the dataset split given for `hi` dataset.
+
+```python
+DatasetDict({
+    train: Dataset({
+        features: ['premise', 'hypothesis', 'label'],
+        num_rows: 392702
+    })
+    test: Dataset({
+        features: ['premise', 'hypothesis', 'label'],
+        num_rows: 5010
+    })
+    validation: Dataset({
+        features: ['premise', 'hypothesis', 'label'],
+        num_rows: 2490
+    })
+})
+
+``` -->
+
+Language      | ISO 639-1 Code |Train | Dev | Test |
+--------------|----------------|-------|-----|------|
+Assamese | as | 392,702 | 5,010 | 2,490 |
+Bengali | bn | 392,702 | 5,010 | 2,490 |
+Gujarati | gu |  392,702 | 5,010 | 2,490 |
+Hindi | hi | 392,702 | 5,010 | 2,490 |
+Kannada | kn |  392,702 | 5,010 | 2,490 |
+Malayalam | ml |392,702  | 5,010 | 2,490 |
+Marathi | mr |392,702 | 5,010 | 2,490 |
+Oriya | or | 392,702 | 5,010 | 2,490 |
+Punjabi | pa | 392,702 | 5,010 | 2,490 |
+Tamil | ta | 392,702 | 5,010 | 2,490 |
+Telugu | te | 392,702 | 5,010 | 2,490 |
+
+<!-- The dataset split remains same across all languages. -->
+
+## Dataset usage
+
+Code snippet for using the dataset using datasets library.
+
+```python
+from datasets import load_dataset
+
+dataset = load_dataset("Divyanshu/indicxnli")
+```
+
+## Dataset Creation
+
+Machine translation of XNLI english dataset to 11 listed Indic Languages.
+
+### Curation Rationale
+
+[More information needed]
+
+### Source Data
+
+[XNLI dataset](https://cims.nyu.edu/~sbowman/xnli/)
+
+#### Initial Data Collection and Normalization
+
+[Detailed in the paper](https://arxiv.org/abs/2204.08776)
+
+#### Who are the source language producers?
+
+[Detailed in the paper](https://arxiv.org/abs/2204.08776)
+
+#### Human Verification Process
+
+[Detailed in the paper](https://arxiv.org/abs/2204.08776)
+
+## Considerations for Using the Data
+
+### Social Impact of Dataset
+
+[Detailed in the paper](https://arxiv.org/abs/2204.08776)
+
+### Discussion of Biases
+
+[Detailed in the paper](https://arxiv.org/abs/2204.08776)
+
+### Other Known Limitations
+
+[Detailed in the paper](https://arxiv.org/abs/2204.08776)
+
+### Dataset Curators
+
+Divyanshu Aggarwal, Vivek Gupta, Anoop Kunchukuttan
+
+### Licensing Information
+
+Contents of this repository are restricted to only non-commercial research purposes under the [Creative Commons Attribution-NonCommercial 4.0 International License (CC BY-NC 4.0)](https://creativecommons.org/licenses/by-nc/4.0/). Copyright of the dataset contents belongs to the original copyright holders.
+
+### Citation Information
+
+If you use any of the datasets, models or code modules, please cite the following paper:
+
+```
+@misc{https://doi.org/10.48550/arxiv.2204.08776,
+  doi = {10.48550/ARXIV.2204.08776},
+  
+  url = {https://arxiv.org/abs/2204.08776},
+  
+  author = {Aggarwal, Divyanshu and Gupta, Vivek and Kunchukuttan, Anoop},
+  
+  keywords = {Computation and Language (cs.CL), Artificial Intelligence (cs.AI), FOS: Computer and information sciences, FOS: Computer and information sciences},
+  
+  title = {IE-SemParse: Evaluating Multilingual Inference for Indian Languages}, 
+  
+  publisher = {arXiv},
+  
+  year = {2022},
+  
+  copyright = {Creative Commons Attribution 4.0 International}
+}
+```
+
+<!-- ### Contributions -->

.history/README_20230707233641.md

@@ -0,0 +1,234 @@
+---
+annotations_creators:
+- machine-generated
+language_creators:
+- machine-generated
+language:
+- as
+- bn
+- gu
+- hi
+- kn
+- ml
+- mr
+- or
+- pa
+- ta
+- te
+license:
+- cc0-1.0
+multilinguality:
+- multilingual
+pretty_name: IE-SemParse
+size_categories:
+- 1M<n<10M
+source_datasets:
+- original
+task_categories:
+- text2text
+task_ids:
+- Semantic-Parsing
+---
+
+# Dataset Card for "IE-SemParse"
+
+## Table of Contents
+
+- [Dataset Card for "IE-SemParse"](#dataset-card-for-ie-semparse)
+  - [Table of Contents](#table-of-contents)
+  - [Dataset Description](#dataset-description)
+    - [Dataset Summary](#dataset-summary)
+    - [Supported Tasks and Leaderboards](#supported-tasks-and-leaderboards)
+    - [Languages](#languages)
+  - [Dataset Structure](#dataset-structure)
+    - [Data Instances](#data-instances)
+    - [Data Fields](#data-fields)
+    - [Data Splits](#data-splits)
+  - [Dataset usage](#dataset-usage)
+  - [Dataset Creation](#dataset-creation)
+    - [Curation Rationale](#curation-rationale)
+    - [Source Data](#source-data)
+      - [Initial Data Collection and Normalization](#initial-data-collection-and-normalization)
+      - [Who are the source language producers?](#who-are-the-source-language-producers)
+      - [Human Verification Process](#human-verification-process)
+  - [Considerations for Using the Data](#considerations-for-using-the-data)
+    - [Social Impact of Dataset](#social-impact-of-dataset)
+    - [Discussion of Biases](#discussion-of-biases)
+    - [Other Known Limitations](#other-known-limitations)
+    - [Dataset Curators](#dataset-curators)
+    - [Licensing Information](#licensing-information)
+    - [Citation Information](#citation-information)
+
+## Dataset Description
+
+- **Homepage:** <https://github.com/divyanshuaggarwal/IE-SemParse>
+- **Paper:** [Evaluating Inter-Bilingual Semantic Parsing for Indian Languages](https://arxiv.org/abs/2304.13005)
+- **Point of Contact:** [Divyanshu Aggarwal](mailto:[email protected])
+
+### Dataset Summary
+
+INDICXNLI is similar to existing
+XNLI dataset in shape/form, but focusses on Indic language family. INDICXNLI include NLI
+data for eleven major Indic languages that includes
+Assamese (‘as’), Gujarat (‘gu’), Kannada (‘kn’),
+Malayalam (‘ml’), Marathi (‘mr’), Odia (‘or’),
+Punjabi (‘pa’), Tamil (‘ta’), Telugu (‘te’), Hindi
+(‘hi’), and Bengali (‘bn’).
+
+### Supported Tasks and Leaderboards
+
+**Tasks:** Natural Language Inference
+
+**Leaderboards:** Currently there is no Leaderboard for this dataset.
+
+### Languages
+
+- `Assamese (as)`
+- `Bengali (bn)`
+- `Gujarati (gu)`
+- `Kannada (kn)`
+- `Hindi (hi)`
+- `Malayalam (ml)`
+- `Marathi (mr)`
+- `Oriya (or)`
+- `Punjabi (pa)`
+- `Tamil (ta)`
+- `Telugu (te)`
+
+## Dataset Structure
+
+### Data Instances
+
+One example from the `hi` dataset is given below in JSON format.
+
+  ```python
+ {'premise': 'अवधारणात्मक रूप से क्रीम स्किमिंग के दो बुनियादी आयाम हैं-उत्पाद और भूगोल।',
+ 'hypothesis': 'उत्पाद और भूगोल क्रीम स्किमिंग का काम करते हैं।',
+ 'label': 1 (neutral) }
+  ```
+
+### Data Fields
+
+- `premise (string)`: Premise Sentence
+- `hypothesis (string)`: Hypothesis Sentence
+- `label (integer)`: Integer label `0` if hypothesis `entails` the premise, `2` if hypothesis `negates` the premise and `1` otherwise.
+
+### Data Splits
+
+<!-- Below is the dataset split given for `hi` dataset.
+
+```python
+DatasetDict({
+    train: Dataset({
+        features: ['premise', 'hypothesis', 'label'],
+        num_rows: 392702
+    })
+    test: Dataset({
+        features: ['premise', 'hypothesis', 'label'],
+        num_rows: 5010
+    })
+    validation: Dataset({
+        features: ['premise', 'hypothesis', 'label'],
+        num_rows: 2490
+    })
+})
+
+``` -->
+
+Language      | ISO 639-1 Code |Train | Dev | Test |
+--------------|----------------|-------|-----|------|
+Assamese | as | 392,702 | 5,010 | 2,490 |
+Bengali | bn | 392,702 | 5,010 | 2,490 |
+Gujarati | gu |  392,702 | 5,010 | 2,490 |
+Hindi | hi | 392,702 | 5,010 | 2,490 |
+Kannada | kn |  392,702 | 5,010 | 2,490 |
+Malayalam | ml |392,702  | 5,010 | 2,490 |
+Marathi | mr |392,702 | 5,010 | 2,490 |
+Oriya | or | 392,702 | 5,010 | 2,490 |
+Punjabi | pa | 392,702 | 5,010 | 2,490 |
+Tamil | ta | 392,702 | 5,010 | 2,490 |
+Telugu | te | 392,702 | 5,010 | 2,490 |
+
+<!-- The dataset split remains same across all languages. -->
+
+## Dataset usage
+
+Code snippet for using the dataset using datasets library.
+
+```python
+from datasets import load_dataset
+
+dataset = load_dataset("Divyanshu/indicxnli")
+```
+
+## Dataset Creation
+
+Machine translation of XNLI english dataset to 11 listed Indic Languages.
+
+### Curation Rationale
+
+[More information needed]
+
+### Source Data
+
+[XNLI dataset](https://cims.nyu.edu/~sbowman/xnli/)
+
+#### Initial Data Collection and Normalization
+
+[Detailed in the paper](https://arxiv.org/abs/2304.13005)
+
+#### Who are the source language producers?
+
+[Detailed in the paper](https://arxiv.org/abs/2304.13005)
+
+#### Human Verification Process
+
+[Detailed in the paper](https://arxiv.org/abs/2304.13005)
+
+## Considerations for Using the Data
+
+### Social Impact of Dataset
+
+[Detailed in the paper](https://arxiv.org/abs/2304.13005)
+
+### Discussion of Biases
+
+[Detailed in the paper](https://arxiv.org/abs/2304.13005)
+
+### Other Known Limitations
+
+[Detailed in the paper](https://arxiv.org/abs/2304.13005)
+
+### Dataset Curators
+
+Divyanshu Aggarwal, Vivek Gupta, Anoop Kunchukuttan
+
+### Licensing Information
+
+Contents of this repository are restricted to only non-commercial research purposes under the [Creative Commons Attribution-NonCommercial 4.0 International License (CC BY-NC 4.0)](https://creativecommons.org/licenses/by-nc/4.0/). Copyright of the dataset contents belongs to the original copyright holders.
+
+### Citation Information
+
+If you use any of the datasets, models or code modules, please cite the following paper:
+
+```
+@misc{https://doi.org/10.48550/arxiv.2204.08776,
+  doi = {10.48550/ARXIV.2204.08776},
+  
+  url = {https://arxiv.org/abs/2304.13005},
+  
+  author = {Aggarwal, Divyanshu and Gupta, Vivek and Kunchukuttan, Anoop},
+  
+  keywords = {Computation and Language (cs.CL), Artificial Intelligence (cs.AI), FOS: Computer and information sciences, FOS: Computer and information sciences},
+  
+  title = {IE-SemParse: Evaluating Multilingual Inference for Indian Languages}, 
+  
+  publisher = {arXiv},
+  
+  year = {2022},
+  
+  copyright = {Creative Commons Attribution 4.0 International}
+}
+```
+
+<!-- ### Contributions -->

.history/README_20230707233647.md

@@ -0,0 +1,234 @@
+---
+annotations_creators:
+- machine-generated
+language_creators:
+- machine-generated
+language:
+- as
+- bn
+- gu
+- hi
+- kn
+- ml
+- mr
+- or
+- pa
+- ta
+- te
+license:
+- cc0-1.0
+multilinguality:
+- multilingual
+pretty_name: IE-SemParse
+size_categories:
+- 1M<n<10M
+source_datasets:
+- original
+task_categories:
+- text2text
+task_ids:
+- Semantic-Parsing
+---
+
+# Dataset Card for "IE-SemParse"
+
+## Table of Contents
+
+- [Dataset Card for "IE-SemParse"](#dataset-card-for-ie-semparse)
+  - [Table of Contents](#table-of-contents)
+  - [Dataset Description](#dataset-description)
+    - [Dataset Summary](#dataset-summary)
+    - [Supported Tasks and Leaderboards](#supported-tasks-and-leaderboards)
+    - [Languages](#languages)
+  - [Dataset Structure](#dataset-structure)
+    - [Data Instances](#data-instances)
+    - [Data Fields](#data-fields)
+    - [Data Splits](#data-splits)
+  - [Dataset usage](#dataset-usage)
+  - [Dataset Creation](#dataset-creation)
+    - [Curation Rationale](#curation-rationale)
+    - [Source Data](#source-data)
+      - [Initial Data Collection and Normalization](#initial-data-collection-and-normalization)
+      - [Who are the source language producers?](#who-are-the-source-language-producers)
+      - [Human Verification Process](#human-verification-process)
+  - [Considerations for Using the Data](#considerations-for-using-the-data)
+    - [Social Impact of Dataset](#social-impact-of-dataset)
+    - [Discussion of Biases](#discussion-of-biases)
+    - [Other Known Limitations](#other-known-limitations)
+    - [Dataset Curators](#dataset-curators)
+    - [Licensing Information](#licensing-information)
+    - [Citation Information](#citation-information)
+
+## Dataset Description
+
+- **Homepage:** <https://github.com/divyanshuaggarwal/IE-SemParse>
+- **Paper:** [Evaluating Inter-Bilingual Semantic Parsing for Indian Languages](https://arxiv.org/abs/2304.13005)
+- **Point of Contact:** [Divyanshu Aggarwal](mailto:[email protected])
+
+### Dataset Summary
+
+IE-SemParse is similar to existing
+XNLI dataset in shape/form, but focusses on Indic language family. INDICXNLI include NLI
+data for eleven major Indic languages that includes
+Assamese (‘as’), Gujarat (‘gu’), Kannada (‘kn’),
+Malayalam (‘ml’), Marathi (‘mr’), Odia (‘or’),
+Punjabi (‘pa’), Tamil (‘ta’), Telugu (‘te’), Hindi
+(‘hi’), and Bengali (‘bn’).
+
+### Supported Tasks and Leaderboards
+
+**Tasks:** Natural Language Inference
+
+**Leaderboards:** Currently there is no Leaderboard for this dataset.
+
+### Languages
+
+- `Assamese (as)`
+- `Bengali (bn)`
+- `Gujarati (gu)`
+- `Kannada (kn)`
+- `Hindi (hi)`
+- `Malayalam (ml)`
+- `Marathi (mr)`
+- `Oriya (or)`
+- `Punjabi (pa)`
+- `Tamil (ta)`
+- `Telugu (te)`
+
+## Dataset Structure
+
+### Data Instances
+
+One example from the `hi` dataset is given below in JSON format.
+
+  ```python
+ {'premise': 'अवधारणात्मक रूप से क्रीम स्किमिंग के दो बुनियादी आयाम हैं-उत्पाद और भूगोल।',
+ 'hypothesis': 'उत्पाद और भूगोल क्रीम स्किमिंग का काम करते हैं।',
+ 'label': 1 (neutral) }
+  ```
+
+### Data Fields
+
+- `premise (string)`: Premise Sentence
+- `hypothesis (string)`: Hypothesis Sentence
+- `label (integer)`: Integer label `0` if hypothesis `entails` the premise, `2` if hypothesis `negates` the premise and `1` otherwise.
+
+### Data Splits
+
+<!-- Below is the dataset split given for `hi` dataset.
+
+```python
+DatasetDict({
+    train: Dataset({
+        features: ['premise', 'hypothesis', 'label'],
+        num_rows: 392702
+    })
+    test: Dataset({
+        features: ['premise', 'hypothesis', 'label'],
+        num_rows: 5010
+    })
+    validation: Dataset({
+        features: ['premise', 'hypothesis', 'label'],
+        num_rows: 2490
+    })
+})
+
+``` -->
+
+Language      | ISO 639-1 Code |Train | Dev | Test |
+--------------|----------------|-------|-----|------|
+Assamese | as | 392,702 | 5,010 | 2,490 |
+Bengali | bn | 392,702 | 5,010 | 2,490 |
+Gujarati | gu |  392,702 | 5,010 | 2,490 |
+Hindi | hi | 392,702 | 5,010 | 2,490 |
+Kannada | kn |  392,702 | 5,010 | 2,490 |
+Malayalam | ml |392,702  | 5,010 | 2,490 |
+Marathi | mr |392,702 | 5,010 | 2,490 |
+Oriya | or | 392,702 | 5,010 | 2,490 |
+Punjabi | pa | 392,702 | 5,010 | 2,490 |
+Tamil | ta | 392,702 | 5,010 | 2,490 |
+Telugu | te | 392,702 | 5,010 | 2,490 |
+
+<!-- The dataset split remains same across all languages. -->
+
+## Dataset usage
+
+Code snippet for using the dataset using datasets library.
+
+```python
+from datasets import load_dataset
+
+dataset = load_dataset("Divyanshu/indicxnli")
+```
+
+## Dataset Creation
+
+Machine translation of XNLI english dataset to 11 listed Indic Languages.
+
+### Curation Rationale
+
+[More information needed]
+
+### Source Data
+
+[XNLI dataset](https://cims.nyu.edu/~sbowman/xnli/)
+
+#### Initial Data Collection and Normalization
+
+[Detailed in the paper](https://arxiv.org/abs/2304.13005)
+
+#### Who are the source language producers?
+
+[Detailed in the paper](https://arxiv.org/abs/2304.13005)
+
+#### Human Verification Process
+
+[Detailed in the paper](https://arxiv.org/abs/2304.13005)
+
+## Considerations for Using the Data
+
+### Social Impact of Dataset
+
+[Detailed in the paper](https://arxiv.org/abs/2304.13005)
+
+### Discussion of Biases
+
+[Detailed in the paper](https://arxiv.org/abs/2304.13005)
+
+### Other Known Limitations
+
+[Detailed in the paper](https://arxiv.org/abs/2304.13005)
+
+### Dataset Curators
+
+Divyanshu Aggarwal, Vivek Gupta, Anoop Kunchukuttan
+
+### Licensing Information
+
+Contents of this repository are restricted to only non-commercial research purposes under the [Creative Commons Attribution-NonCommercial 4.0 International License (CC BY-NC 4.0)](https://creativecommons.org/licenses/by-nc/4.0/). Copyright of the dataset contents belongs to the original copyright holders.
+
+### Citation Information
+
+If you use any of the datasets, models or code modules, please cite the following paper:
+
+```
+@misc{https://doi.org/10.48550/arxiv.2204.08776,
+  doi = {10.48550/ARXIV.2204.08776},
+  
+  url = {https://arxiv.org/abs/2304.13005},
+  
+  author = {Aggarwal, Divyanshu and Gupta, Vivek and Kunchukuttan, Anoop},
+  
+  keywords = {Computation and Language (cs.CL), Artificial Intelligence (cs.AI), FOS: Computer and information sciences, FOS: Computer and information sciences},
+  
+  title = {IE-SemParse: Evaluating Multilingual Inference for Indian Languages}, 
+  
+  publisher = {arXiv},
+  
+  year = {2022},
+  
+  copyright = {Creative Commons Attribution 4.0 International}
+}
+```
+
+<!-- ### Contributions -->

.history/README_20230707233654.md

@@ -0,0 +1,232 @@
+---
+annotations_creators:
+- machine-generated
+language_creators:
+- machine-generated
+language:
+- as
+- bn
+- gu
+- hi
+- kn
+- ml
+- mr
+- or
+- pa
+- ta
+- te
+license:
+- cc0-1.0
+multilinguality:
+- multilingual
+pretty_name: IE-SemParse
+size_categories:
+- 1M<n<10M
+source_datasets:
+- original
+task_categories:
+- text2text
+task_ids:
+- Semantic-Parsing
+---
+
+# Dataset Card for "IE-SemParse"
+
+## Table of Contents
+
+- [Dataset Card for "IE-SemParse"](#dataset-card-for-ie-semparse)
+  - [Table of Contents](#table-of-contents)
+  - [Dataset Description](#dataset-description)
+    - [Dataset Summary](#dataset-summary)
+    - [Supported Tasks and Leaderboards](#supported-tasks-and-leaderboards)
+    - [Languages](#languages)
+  - [Dataset Structure](#dataset-structure)
+    - [Data Instances](#data-instances)
+    - [Data Fields](#data-fields)
+    - [Data Splits](#data-splits)
+  - [Dataset usage](#dataset-usage)
+  - [Dataset Creation](#dataset-creation)
+    - [Curation Rationale](#curation-rationale)
+    - [Source Data](#source-data)
+      - [Initial Data Collection and Normalization](#initial-data-collection-and-normalization)
+      - [Who are the source language producers?](#who-are-the-source-language-producers)
+      - [Human Verification Process](#human-verification-process)
+  - [Considerations for Using the Data](#considerations-for-using-the-data)
+    - [Social Impact of Dataset](#social-impact-of-dataset)
+    - [Discussion of Biases](#discussion-of-biases)
+    - [Other Known Limitations](#other-known-limitations)
+    - [Dataset Curators](#dataset-curators)
+    - [Licensing Information](#licensing-information)
+    - [Citation Information](#citation-information)
+
+## Dataset Description
+
+- **Homepage:** <https://github.com/divyanshuaggarwal/IE-SemParse>
+- **Paper:** [Evaluating Inter-Bilingual Semantic Parsing for Indian Languages](https://arxiv.org/abs/2304.13005)
+- **Point of Contact:** [Divyanshu Aggarwal](mailto:[email protected])
+
+### Dataset Summary
+
+IE-SemParse is a eleven major Indic languages that includes
+Assamese (‘as’), Gujarat (‘gu’), Kannada (‘kn’),
+Malayalam (‘ml’), Marathi (‘mr’), Odia (‘or’),
+Punjabi (‘pa’), Tamil (‘ta’), Telugu (‘te’), Hindi
+(‘hi’), and Bengali (‘bn’).
+
+### Supported Tasks and Leaderboards
+
+**Tasks:** Natural Language Inference
+
+**Leaderboards:** Currently there is no Leaderboard for this dataset.
+
+### Languages
+
+- `Assamese (as)`
+- `Bengali (bn)`
+- `Gujarati (gu)`
+- `Kannada (kn)`
+- `Hindi (hi)`
+- `Malayalam (ml)`
+- `Marathi (mr)`
+- `Oriya (or)`
+- `Punjabi (pa)`
+- `Tamil (ta)`
+- `Telugu (te)`
+
+## Dataset Structure
+
+### Data Instances
+
+One example from the `hi` dataset is given below in JSON format.
+
+  ```python
+ {'premise': 'अवधारणात्मक रूप से क्रीम स्किमिंग के दो बुनियादी आयाम हैं-उत्पाद और भूगोल।',
+ 'hypothesis': 'उत्पाद और भूगोल क्रीम स्किमिंग का काम करते हैं।',
+ 'label': 1 (neutral) }
+  ```
+
+### Data Fields
+
+- `premise (string)`: Premise Sentence
+- `hypothesis (string)`: Hypothesis Sentence
+- `label (integer)`: Integer label `0` if hypothesis `entails` the premise, `2` if hypothesis `negates` the premise and `1` otherwise.
+
+### Data Splits
+
+<!-- Below is the dataset split given for `hi` dataset.
+
+```python
+DatasetDict({
+    train: Dataset({
+        features: ['premise', 'hypothesis', 'label'],
+        num_rows: 392702
+    })
+    test: Dataset({
+        features: ['premise', 'hypothesis', 'label'],
+        num_rows: 5010
+    })
+    validation: Dataset({
+        features: ['premise', 'hypothesis', 'label'],
+        num_rows: 2490
+    })
+})
+
+``` -->
+
+Language      | ISO 639-1 Code |Train | Dev | Test |
+--------------|----------------|-------|-----|------|
+Assamese | as | 392,702 | 5,010 | 2,490 |
+Bengali | bn | 392,702 | 5,010 | 2,490 |
+Gujarati | gu |  392,702 | 5,010 | 2,490 |
+Hindi | hi | 392,702 | 5,010 | 2,490 |
+Kannada | kn |  392,702 | 5,010 | 2,490 |
+Malayalam | ml |392,702  | 5,010 | 2,490 |
+Marathi | mr |392,702 | 5,010 | 2,490 |
+Oriya | or | 392,702 | 5,010 | 2,490 |
+Punjabi | pa | 392,702 | 5,010 | 2,490 |
+Tamil | ta | 392,702 | 5,010 | 2,490 |
+Telugu | te | 392,702 | 5,010 | 2,490 |
+
+<!-- The dataset split remains same across all languages. -->
+
+## Dataset usage
+
+Code snippet for using the dataset using datasets library.
+
+```python
+from datasets import load_dataset
+
+dataset = load_dataset("Divyanshu/indicxnli")
+```
+
+## Dataset Creation
+
+Machine translation of XNLI english dataset to 11 listed Indic Languages.
+
+### Curation Rationale
+
+[More information needed]
+
+### Source Data
+
+[XNLI dataset](https://cims.nyu.edu/~sbowman/xnli/)
+
+#### Initial Data Collection and Normalization
+
+[Detailed in the paper](https://arxiv.org/abs/2304.13005)
+
+#### Who are the source language producers?
+
+[Detailed in the paper](https://arxiv.org/abs/2304.13005)
+
+#### Human Verification Process
+
+[Detailed in the paper](https://arxiv.org/abs/2304.13005)
+
+## Considerations for Using the Data
+
+### Social Impact of Dataset
+
+[Detailed in the paper](https://arxiv.org/abs/2304.13005)
+
+### Discussion of Biases
+
+[Detailed in the paper](https://arxiv.org/abs/2304.13005)
+
+### Other Known Limitations
+
+[Detailed in the paper](https://arxiv.org/abs/2304.13005)
+
+### Dataset Curators
+
+Divyanshu Aggarwal, Vivek Gupta, Anoop Kunchukuttan
+
+### Licensing Information
+
+Contents of this repository are restricted to only non-commercial research purposes under the [Creative Commons Attribution-NonCommercial 4.0 International License (CC BY-NC 4.0)](https://creativecommons.org/licenses/by-nc/4.0/). Copyright of the dataset contents belongs to the original copyright holders.
+
+### Citation Information
+
+If you use any of the datasets, models or code modules, please cite the following paper:
+
+```
+@misc{https://doi.org/10.48550/arxiv.2204.08776,
+  doi = {10.48550/ARXIV.2204.08776},
+  
+  url = {https://arxiv.org/abs/2304.13005},
+  
+  author = {Aggarwal, Divyanshu and Gupta, Vivek and Kunchukuttan, Anoop},
+  
+  keywords = {Computation and Language (cs.CL), Artificial Intelligence (cs.AI), FOS: Computer and information sciences, FOS: Computer and information sciences},
+  
+  title = {IE-SemParse: Evaluating Multilingual Inference for Indian Languages}, 
+  
+  publisher = {arXiv},
+  
+  year = {2022},
+  
+  copyright = {Creative Commons Attribution 4.0 International}
+}
+```
+
+<!-- ### Contributions -->

.history/README_20230707233704.md

@@ -0,0 +1,232 @@
+---
+annotations_creators:
+- machine-generated
+language_creators:
+- machine-generated
+language:
+- as
+- bn
+- gu
+- hi
+- kn
+- ml
+- mr
+- or
+- pa
+- ta
+- te
+license:
+- cc0-1.0
+multilinguality:
+- multilingual
+pretty_name: IE-SemParse
+size_categories:
+- 1M<n<10M
+source_datasets:
+- original
+task_categories:
+- text2text
+task_ids:
+- Semantic-Parsing
+---
+
+# Dataset Card for "IE-SemParse"
+
+## Table of Contents
+
+- [Dataset Card for "IE-SemParse"](#dataset-card-for-ie-semparse)
+  - [Table of Contents](#table-of-contents)
+  - [Dataset Description](#dataset-description)
+    - [Dataset Summary](#dataset-summary)
+    - [Supported Tasks and Leaderboards](#supported-tasks-and-leaderboards)
+    - [Languages](#languages)
+  - [Dataset Structure](#dataset-structure)
+    - [Data Instances](#data-instances)
+    - [Data Fields](#data-fields)
+    - [Data Splits](#data-splits)
+  - [Dataset usage](#dataset-usage)
+  - [Dataset Creation](#dataset-creation)
+    - [Curation Rationale](#curation-rationale)
+    - [Source Data](#source-data)
+      - [Initial Data Collection and Normalization](#initial-data-collection-and-normalization)
+      - [Who are the source language producers?](#who-are-the-source-language-producers)
+      - [Human Verification Process](#human-verification-process)
+  - [Considerations for Using the Data](#considerations-for-using-the-data)
+    - [Social Impact of Dataset](#social-impact-of-dataset)
+    - [Discussion of Biases](#discussion-of-biases)
+    - [Other Known Limitations](#other-known-limitations)
+    - [Dataset Curators](#dataset-curators)
+    - [Licensing Information](#licensing-information)
+    - [Citation Information](#citation-information)
+
+## Dataset Description
+
+- **Homepage:** <https://github.com/divyanshuaggarwal/IE-SemParse>
+- **Paper:** [Evaluating Inter-Bilingual Semantic Parsing for Indian Languages](https://arxiv.org/abs/2304.13005)
+- **Point of Contact:** [Divyanshu Aggarwal](mailto:[email protected])
+
+### Dataset Summary
+
+IE-SemParse is an InterBilingual Semantic eleven major Indic languages that includes
+Assamese (‘as’), Gujarat (‘gu’), Kannada (‘kn’),
+Malayalam (‘ml’), Marathi (‘mr’), Odia (‘or’),
+Punjabi (‘pa’), Tamil (‘ta’), Telugu (‘te’), Hindi
+(‘hi’), and Bengali (‘bn’).
+
+### Supported Tasks and Leaderboards
+
+**Tasks:** Natural Language Inference
+
+**Leaderboards:** Currently there is no Leaderboard for this dataset.
+
+### Languages
+
+- `Assamese (as)`
+- `Bengali (bn)`
+- `Gujarati (gu)`
+- `Kannada (kn)`
+- `Hindi (hi)`
+- `Malayalam (ml)`
+- `Marathi (mr)`
+- `Oriya (or)`
+- `Punjabi (pa)`
+- `Tamil (ta)`
+- `Telugu (te)`
+
+## Dataset Structure
+
+### Data Instances
+
+One example from the `hi` dataset is given below in JSON format.
+
+  ```python
+ {'premise': 'अवधारणात्मक रूप से क्रीम स्किमिंग के दो बुनियादी आयाम हैं-उत्पाद और भूगोल।',
+ 'hypothesis': 'उत्पाद और भूगोल क्रीम स्किमिंग का काम करते हैं।',
+ 'label': 1 (neutral) }
+  ```
+
+### Data Fields
+
+- `premise (string)`: Premise Sentence
+- `hypothesis (string)`: Hypothesis Sentence
+- `label (integer)`: Integer label `0` if hypothesis `entails` the premise, `2` if hypothesis `negates` the premise and `1` otherwise.
+
+### Data Splits
+
+<!-- Below is the dataset split given for `hi` dataset.
+
+```python
+DatasetDict({
+    train: Dataset({
+        features: ['premise', 'hypothesis', 'label'],
+        num_rows: 392702
+    })
+    test: Dataset({
+        features: ['premise', 'hypothesis', 'label'],
+        num_rows: 5010
+    })
+    validation: Dataset({
+        features: ['premise', 'hypothesis', 'label'],
+        num_rows: 2490
+    })
+})
+
+``` -->
+
+Language      | ISO 639-1 Code |Train | Dev | Test |
+--------------|----------------|-------|-----|------|
+Assamese | as | 392,702 | 5,010 | 2,490 |
+Bengali | bn | 392,702 | 5,010 | 2,490 |
+Gujarati | gu |  392,702 | 5,010 | 2,490 |
+Hindi | hi | 392,702 | 5,010 | 2,490 |
+Kannada | kn |  392,702 | 5,010 | 2,490 |
+Malayalam | ml |392,702  | 5,010 | 2,490 |
+Marathi | mr |392,702 | 5,010 | 2,490 |
+Oriya | or | 392,702 | 5,010 | 2,490 |
+Punjabi | pa | 392,702 | 5,010 | 2,490 |
+Tamil | ta | 392,702 | 5,010 | 2,490 |
+Telugu | te | 392,702 | 5,010 | 2,490 |
+
+<!-- The dataset split remains same across all languages. -->
+
+## Dataset usage
+
+Code snippet for using the dataset using datasets library.
+
+```python
+from datasets import load_dataset
+
+dataset = load_dataset("Divyanshu/indicxnli")
+```
+
+## Dataset Creation
+
+Machine translation of XNLI english dataset to 11 listed Indic Languages.
+
+### Curation Rationale
+
+[More information needed]
+
+### Source Data
+
+[XNLI dataset](https://cims.nyu.edu/~sbowman/xnli/)
+
+#### Initial Data Collection and Normalization
+
+[Detailed in the paper](https://arxiv.org/abs/2304.13005)
+
+#### Who are the source language producers?
+
+[Detailed in the paper](https://arxiv.org/abs/2304.13005)
+
+#### Human Verification Process
+
+[Detailed in the paper](https://arxiv.org/abs/2304.13005)
+
+## Considerations for Using the Data
+
+### Social Impact of Dataset
+
+[Detailed in the paper](https://arxiv.org/abs/2304.13005)
+
+### Discussion of Biases
+
+[Detailed in the paper](https://arxiv.org/abs/2304.13005)
+
+### Other Known Limitations
+
+[Detailed in the paper](https://arxiv.org/abs/2304.13005)
+
+### Dataset Curators
+
+Divyanshu Aggarwal, Vivek Gupta, Anoop Kunchukuttan
+
+### Licensing Information
+
+Contents of this repository are restricted to only non-commercial research purposes under the [Creative Commons Attribution-NonCommercial 4.0 International License (CC BY-NC 4.0)](https://creativecommons.org/licenses/by-nc/4.0/). Copyright of the dataset contents belongs to the original copyright holders.
+
+### Citation Information
+
+If you use any of the datasets, models or code modules, please cite the following paper:
+
+```
+@misc{https://doi.org/10.48550/arxiv.2204.08776,
+  doi = {10.48550/ARXIV.2204.08776},
+  
+  url = {https://arxiv.org/abs/2304.13005},
+  
+  author = {Aggarwal, Divyanshu and Gupta, Vivek and Kunchukuttan, Anoop},
+  
+  keywords = {Computation and Language (cs.CL), Artificial Intelligence (cs.AI), FOS: Computer and information sciences, FOS: Computer and information sciences},
+  
+  title = {IE-SemParse: Evaluating Multilingual Inference for Indian Languages}, 
+  
+  publisher = {arXiv},
+  
+  year = {2022},
+  
+  copyright = {Creative Commons Attribution 4.0 International}
+}
+```
+
+<!-- ### Contributions -->

.history/README_20230707233708.md

@@ -0,0 +1,232 @@
+---
+annotations_creators:
+- machine-generated
+language_creators:
+- machine-generated
+language:
+- as
+- bn
+- gu
+- hi
+- kn
+- ml
+- mr
+- or
+- pa
+- ta
+- te
+license:
+- cc0-1.0
+multilinguality:
+- multilingual
+pretty_name: IE-SemParse
+size_categories:
+- 1M<n<10M
+source_datasets:
+- original
+task_categories:
+- text2text
+task_ids:
+- Semantic-Parsing
+---
+
+# Dataset Card for "IE-SemParse"
+
+## Table of Contents
+
+- [Dataset Card for "IE-SemParse"](#dataset-card-for-ie-semparse)
+  - [Table of Contents](#table-of-contents)
+  - [Dataset Description](#dataset-description)
+    - [Dataset Summary](#dataset-summary)
+    - [Supported Tasks and Leaderboards](#supported-tasks-and-leaderboards)
+    - [Languages](#languages)
+  - [Dataset Structure](#dataset-structure)
+    - [Data Instances](#data-instances)
+    - [Data Fields](#data-fields)
+    - [Data Splits](#data-splits)
+  - [Dataset usage](#dataset-usage)
+  - [Dataset Creation](#dataset-creation)
+    - [Curation Rationale](#curation-rationale)
+    - [Source Data](#source-data)
+      - [Initial Data Collection and Normalization](#initial-data-collection-and-normalization)
+      - [Who are the source language producers?](#who-are-the-source-language-producers)
+      - [Human Verification Process](#human-verification-process)
+  - [Considerations for Using the Data](#considerations-for-using-the-data)
+    - [Social Impact of Dataset](#social-impact-of-dataset)
+    - [Discussion of Biases](#discussion-of-biases)
+    - [Other Known Limitations](#other-known-limitations)
+    - [Dataset Curators](#dataset-curators)
+    - [Licensing Information](#licensing-information)
+    - [Citation Information](#citation-information)
+
+## Dataset Description
+
+- **Homepage:** <https://github.com/divyanshuaggarwal/IE-SemParse>
+- **Paper:** [Evaluating Inter-Bilingual Semantic Parsing for Indian Languages](https://arxiv.org/abs/2304.13005)
+- **Point of Contact:** [Divyanshu Aggarwal](mailto:[email protected])
+
+### Dataset Summary
+
+IE-SemParse is an InterBilingual Semantic Parsing Dataset for eleven major Indic languages that includes
+Assamese (‘as’), Gujarat (‘gu’), Kannada (‘kn’),
+Malayalam (‘ml’), Marathi (‘mr’), Odia (‘or’),
+Punjabi (‘pa’), Tamil (‘ta’), Telugu (‘te’), Hindi
+(‘hi’), and Bengali (‘bn’).
+
+### Supported Tasks and Leaderboards
+
+**Tasks:** Natural Language Inference
+
+**Leaderboards:** Currently there is no Leaderboard for this dataset.
+
+### Languages
+
+- `Assamese (as)`
+- `Bengali (bn)`
+- `Gujarati (gu)`
+- `Kannada (kn)`
+- `Hindi (hi)`
+- `Malayalam (ml)`
+- `Marathi (mr)`
+- `Oriya (or)`
+- `Punjabi (pa)`
+- `Tamil (ta)`
+- `Telugu (te)`
+
+## Dataset Structure
+
+### Data Instances
+
+One example from the `hi` dataset is given below in JSON format.
+
+  ```python
+ {'premise': 'अवधारणात्मक रूप से क्रीम स्किमिंग के दो बुनियादी आयाम हैं-उत्पाद और भूगोल।',
+ 'hypothesis': 'उत्पाद और भूगोल क्रीम स्किमिंग का काम करते हैं।',
+ 'label': 1 (neutral) }
+  ```
+
+### Data Fields
+
+- `premise (string)`: Premise Sentence
+- `hypothesis (string)`: Hypothesis Sentence
+- `label (integer)`: Integer label `0` if hypothesis `entails` the premise, `2` if hypothesis `negates` the premise and `1` otherwise.
+
+### Data Splits
+
+<!-- Below is the dataset split given for `hi` dataset.
+
+```python
+DatasetDict({
+    train: Dataset({
+        features: ['premise', 'hypothesis', 'label'],
+        num_rows: 392702
+    })
+    test: Dataset({
+        features: ['premise', 'hypothesis', 'label'],
+        num_rows: 5010
+    })
+    validation: Dataset({
+        features: ['premise', 'hypothesis', 'label'],
+        num_rows: 2490
+    })
+})
+
+``` -->
+
+Language      | ISO 639-1 Code |Train | Dev | Test |
+--------------|----------------|-------|-----|------|
+Assamese | as | 392,702 | 5,010 | 2,490 |
+Bengali | bn | 392,702 | 5,010 | 2,490 |
+Gujarati | gu |  392,702 | 5,010 | 2,490 |
+Hindi | hi | 392,702 | 5,010 | 2,490 |
+Kannada | kn |  392,702 | 5,010 | 2,490 |
+Malayalam | ml |392,702  | 5,010 | 2,490 |
+Marathi | mr |392,702 | 5,010 | 2,490 |
+Oriya | or | 392,702 | 5,010 | 2,490 |
+Punjabi | pa | 392,702 | 5,010 | 2,490 |
+Tamil | ta | 392,702 | 5,010 | 2,490 |
+Telugu | te | 392,702 | 5,010 | 2,490 |
+
+<!-- The dataset split remains same across all languages. -->
+
+## Dataset usage
+
+Code snippet for using the dataset using datasets library.
+
+```python
+from datasets import load_dataset
+
+dataset = load_dataset("Divyanshu/indicxnli")
+```
+
+## Dataset Creation
+
+Machine translation of XNLI english dataset to 11 listed Indic Languages.
+
+### Curation Rationale
+
+[More information needed]
+
+### Source Data
+
+[XNLI dataset](https://cims.nyu.edu/~sbowman/xnli/)
+
+#### Initial Data Collection and Normalization
+
+[Detailed in the paper](https://arxiv.org/abs/2304.13005)
+
+#### Who are the source language producers?
+
+[Detailed in the paper](https://arxiv.org/abs/2304.13005)
+
+#### Human Verification Process
+
+[Detailed in the paper](https://arxiv.org/abs/2304.13005)
+
+## Considerations for Using the Data
+
+### Social Impact of Dataset
+
+[Detailed in the paper](https://arxiv.org/abs/2304.13005)
+
+### Discussion of Biases
+
+[Detailed in the paper](https://arxiv.org/abs/2304.13005)
+
+### Other Known Limitations
+
+[Detailed in the paper](https://arxiv.org/abs/2304.13005)
+
+### Dataset Curators
+
+Divyanshu Aggarwal, Vivek Gupta, Anoop Kunchukuttan
+
+### Licensing Information
+
+Contents of this repository are restricted to only non-commercial research purposes under the [Creative Commons Attribution-NonCommercial 4.0 International License (CC BY-NC 4.0)](https://creativecommons.org/licenses/by-nc/4.0/). Copyright of the dataset contents belongs to the original copyright holders.
+
+### Citation Information
+
+If you use any of the datasets, models or code modules, please cite the following paper:
+
+```
+@misc{https://doi.org/10.48550/arxiv.2204.08776,
+  doi = {10.48550/ARXIV.2204.08776},
+  
+  url = {https://arxiv.org/abs/2304.13005},
+  
+  author = {Aggarwal, Divyanshu and Gupta, Vivek and Kunchukuttan, Anoop},
+  
+  keywords = {Computation and Language (cs.CL), Artificial Intelligence (cs.AI), FOS: Computer and information sciences, FOS: Computer and information sciences},
+  
+  title = {IE-SemParse: Evaluating Multilingual Inference for Indian Languages}, 
+  
+  publisher = {arXiv},
+  
+  year = {2022},
+  
+  copyright = {Creative Commons Attribution 4.0 International}
+}
+```
+
+<!-- ### Contributions -->

.history/README_20230707233722.md

@@ -0,0 +1,229 @@
+---
+annotations_creators:
+- machine-generated
+language_creators:
+- machine-generated
+language:
+- as
+- bn
+- gu
+- hi
+- kn
+- ml
+- mr
+- or
+- pa
+- ta
+- te
+license:
+- cc0-1.0
+multilinguality:
+- multilingual
+pretty_name: IE-SemParse
+size_categories:
+- 1M<n<10M
+source_datasets:
+- original
+task_categories:
+- text2text
+task_ids:
+- Semantic-Parsing
+---
+
+# Dataset Card for "IE-SemParse"
+
+## Table of Contents
+
+- [Dataset Card for "IE-SemParse"](#dataset-card-for-ie-semparse)
+  - [Table of Contents](#table-of-contents)
+  - [Dataset Description](#dataset-description)
+    - [Dataset Summary](#dataset-summary)
+    - [Supported Tasks and Leaderboards](#supported-tasks-and-leaderboards)
+    - [Languages](#languages)
+  - [Dataset Structure](#dataset-structure)
+    - [Data Instances](#data-instances)
+    - [Data Fields](#data-fields)
+    - [Data Splits](#data-splits)
+  - [Dataset usage](#dataset-usage)
+  - [Dataset Creation](#dataset-creation)
+    - [Curation Rationale](#curation-rationale)
+    - [Source Data](#source-data)
+      - [Initial Data Collection and Normalization](#initial-data-collection-and-normalization)
+      - [Who are the source language producers?](#who-are-the-source-language-producers)
+      - [Human Verification Process](#human-verification-process)
+  - [Considerations for Using the Data](#considerations-for-using-the-data)
+    - [Social Impact of Dataset](#social-impact-of-dataset)
+    - [Discussion of Biases](#discussion-of-biases)
+    - [Other Known Limitations](#other-known-limitations)
+    - [Dataset Curators](#dataset-curators)
+    - [Licensing Information](#licensing-information)
+    - [Citation Information](#citation-information)
+
+## Dataset Description
+
+- **Homepage:** <https://github.com/divyanshuaggarwal/IE-SemParse>
+- **Paper:** [Evaluating Inter-Bilingual Semantic Parsing for Indian Languages](https://arxiv.org/abs/2304.13005)
+- **Point of Contact:** [Divyanshu Aggarwal](mailto:[email protected])
+
+### Dataset Summary
+
+IE-SemParse is an InterBilingual Semantic Parsing Dataset for eleven major Indic languages that includes
+Assamese (‘as’), Gujarat (‘gu’), Kannada (‘kn’),
+Malayalam (‘ml’), Marathi (‘mr’), Odia (‘or’),
+Punjabi (‘pa’), Tamil (‘ta’), Telugu (‘te’), Hindi
+(‘hi’), and Bengali (‘bn’).
+
+### Supported Tasks and Leaderboards
+
+**Tasks:** Natural Language Inference
+
+**Leaderboards:** Currently there is no Leaderboard for this dataset.
+
+### Languages
+
+- `Assamese (as)`
+- `Bengali (bn)`
+- `Gujarati (gu)`
+- `Kannada (kn)`
+- `Hindi (hi)`
+- `Malayalam (ml)`
+- `Marathi (mr)`
+- `Oriya (or)`
+- `Punjabi (pa)`
+- `Tamil (ta)`
+- `Telugu (te)`
+
+## Dataset Structure
+
+### Data Instances
+
+One example from the `hi` dataset is given below in JSON format.
+
+  ```python
+ {'premise': 'अवधारणात्मक रूप से क्रीम स्किमिंग के दो बुनियादी आयाम हैं-उत्पाद और भूगोल।',
+ 'hypothesis': 'उत्पाद और भूगोल क्रीम स्किमिंग का काम करते हैं।',
+ 'label': 1 (neutral) }
+  ```
+
+### Data Fields
+
+
+### Data Splits
+
+<!-- Below is the dataset split given for `hi` dataset.
+
+```python
+DatasetDict({
+    train: Dataset({
+        features: ['premise', 'hypothesis', 'label'],
+        num_rows: 392702
+    })
+    test: Dataset({
+        features: ['premise', 'hypothesis', 'label'],
+        num_rows: 5010
+    })
+    validation: Dataset({
+        features: ['premise', 'hypothesis', 'label'],
+        num_rows: 2490
+    })
+})
+
+``` -->
+
+Language      | ISO 639-1 Code |Train | Dev | Test |
+--------------|----------------|-------|-----|------|
+Assamese | as | 392,702 | 5,010 | 2,490 |
+Bengali | bn | 392,702 | 5,010 | 2,490 |
+Gujarati | gu |  392,702 | 5,010 | 2,490 |
+Hindi | hi | 392,702 | 5,010 | 2,490 |
+Kannada | kn |  392,702 | 5,010 | 2,490 |
+Malayalam | ml |392,702  | 5,010 | 2,490 |
+Marathi | mr |392,702 | 5,010 | 2,490 |
+Oriya | or | 392,702 | 5,010 | 2,490 |
+Punjabi | pa | 392,702 | 5,010 | 2,490 |
+Tamil | ta | 392,702 | 5,010 | 2,490 |
+Telugu | te | 392,702 | 5,010 | 2,490 |
+
+<!-- The dataset split remains same across all languages. -->
+
+## Dataset usage
+
+Code snippet for using the dataset using datasets library.
+
+```python
+from datasets import load_dataset
+
+dataset = load_dataset("Divyanshu/indicxnli")
+```
+
+## Dataset Creation
+
+Machine translation of XNLI english dataset to 11 listed Indic Languages.
+
+### Curation Rationale
+
+[More information needed]
+
+### Source Data
+
+[XNLI dataset](https://cims.nyu.edu/~sbowman/xnli/)
+
+#### Initial Data Collection and Normalization
+
+[Detailed in the paper](https://arxiv.org/abs/2304.13005)
+
+#### Who are the source language producers?
+
+[Detailed in the paper](https://arxiv.org/abs/2304.13005)
+
+#### Human Verification Process
+
+[Detailed in the paper](https://arxiv.org/abs/2304.13005)
+
+## Considerations for Using the Data
+
+### Social Impact of Dataset
+
+[Detailed in the paper](https://arxiv.org/abs/2304.13005)
+
+### Discussion of Biases
+
+[Detailed in the paper](https://arxiv.org/abs/2304.13005)
+
+### Other Known Limitations
+
+[Detailed in the paper](https://arxiv.org/abs/2304.13005)
+
+### Dataset Curators
+
+Divyanshu Aggarwal, Vivek Gupta, Anoop Kunchukuttan
+
+### Licensing Information
+
+Contents of this repository are restricted to only non-commercial research purposes under the [Creative Commons Attribution-NonCommercial 4.0 International License (CC BY-NC 4.0)](https://creativecommons.org/licenses/by-nc/4.0/). Copyright of the dataset contents belongs to the original copyright holders.
+
+### Citation Information
+
+If you use any of the datasets, models or code modules, please cite the following paper:
+
+```
+@misc{https://doi.org/10.48550/arxiv.2204.08776,
+  doi = {10.48550/ARXIV.2204.08776},
+  
+  url = {https://arxiv.org/abs/2304.13005},
+  
+  author = {Aggarwal, Divyanshu and Gupta, Vivek and Kunchukuttan, Anoop},
+  
+  keywords = {Computation and Language (cs.CL), Artificial Intelligence (cs.AI), FOS: Computer and information sciences, FOS: Computer and information sciences},
+  
+  title = {IE-SemParse: Evaluating Multilingual Inference for Indian Languages}, 
+  
+  publisher = {arXiv},
+  
+  year = {2022},
+  
+  copyright = {Creative Commons Attribution 4.0 International}
+}
+```
+
+<!-- ### Contributions -->

.history/README_20230707233725.md

@@ -0,0 +1,226 @@
+---
+annotations_creators:
+- machine-generated
+language_creators:
+- machine-generated
+language:
+- as
+- bn
+- gu
+- hi
+- kn
+- ml
+- mr
+- or
+- pa
+- ta
+- te
+license:
+- cc0-1.0
+multilinguality:
+- multilingual
+pretty_name: IE-SemParse
+size_categories:
+- 1M<n<10M
+source_datasets:
+- original
+task_categories:
+- text2text
+task_ids:
+- Semantic-Parsing
+---
+
+# Dataset Card for "IE-SemParse"
+
+## Table of Contents
+
+- [Dataset Card for "IE-SemParse"](#dataset-card-for-ie-semparse)
+  - [Table of Contents](#table-of-contents)
+  - [Dataset Description](#dataset-description)
+    - [Dataset Summary](#dataset-summary)
+    - [Supported Tasks and Leaderboards](#supported-tasks-and-leaderboards)
+    - [Languages](#languages)
+  - [Dataset Structure](#dataset-structure)
+    - [Data Instances](#data-instances)
+    - [Data Splits](#data-splits)
+  - [Dataset usage](#dataset-usage)
+  - [Dataset Creation](#dataset-creation)
+    - [Curation Rationale](#curation-rationale)
+    - [Source Data](#source-data)
+      - [Initial Data Collection and Normalization](#initial-data-collection-and-normalization)
+      - [Who are the source language producers?](#who-are-the-source-language-producers)
+      - [Human Verification Process](#human-verification-process)
+  - [Considerations for Using the Data](#considerations-for-using-the-data)
+    - [Social Impact of Dataset](#social-impact-of-dataset)
+    - [Discussion of Biases](#discussion-of-biases)
+    - [Other Known Limitations](#other-known-limitations)
+    - [Dataset Curators](#dataset-curators)
+    - [Licensing Information](#licensing-information)
+    - [Citation Information](#citation-information)
+
+## Dataset Description
+
+- **Homepage:** <https://github.com/divyanshuaggarwal/IE-SemParse>
+- **Paper:** [Evaluating Inter-Bilingual Semantic Parsing for Indian Languages](https://arxiv.org/abs/2304.13005)
+- **Point of Contact:** [Divyanshu Aggarwal](mailto:[email protected])
+
+### Dataset Summary
+
+IE-SemParse is an InterBilingual Semantic Parsing Dataset for eleven major Indic languages that includes
+Assamese (‘as’), Gujarat (‘gu’), Kannada (‘kn’),
+Malayalam (‘ml’), Marathi (‘mr’), Odia (‘or’),
+Punjabi (‘pa’), Tamil (‘ta’), Telugu (‘te’), Hindi
+(‘hi’), and Bengali (‘bn’).
+
+### Supported Tasks and Leaderboards
+
+**Tasks:** Natural Language Inference
+
+**Leaderboards:** Currently there is no Leaderboard for this dataset.
+
+### Languages
+
+- `Assamese (as)`
+- `Bengali (bn)`
+- `Gujarati (gu)`
+- `Kannada (kn)`
+- `Hindi (hi)`
+- `Malayalam (ml)`
+- `Marathi (mr)`
+- `Oriya (or)`
+- `Punjabi (pa)`
+- `Tamil (ta)`
+- `Telugu (te)`
+
+## Dataset Structure
+
+### Data Instances
+
+One example from the `hi` dataset is given below in JSON format.
+
+  ```python
+ {'premise': 'अवधारणात्मक रूप से क्रीम स्किमिंग के दो बुनियादी आयाम हैं-उत्पाद और भूगोल।',
+ 'hypothesis': 'उत्पाद और भूगोल क्रीम स्किमिंग का काम करते हैं।',
+ 'label': 1 (neutral) }
+  ```
+
+
+### Data Splits
+
+<!-- Below is the dataset split given for `hi` dataset.
+
+```python
+DatasetDict({
+    train: Dataset({
+        features: ['premise', 'hypothesis', 'label'],
+        num_rows: 392702
+    })
+    test: Dataset({
+        features: ['premise', 'hypothesis', 'label'],
+        num_rows: 5010
+    })
+    validation: Dataset({
+        features: ['premise', 'hypothesis', 'label'],
+        num_rows: 2490
+    })
+})
+
+``` -->
+
+Language      | ISO 639-1 Code |Train | Dev | Test |
+--------------|----------------|-------|-----|------|
+Assamese | as | 392,702 | 5,010 | 2,490 |
+Bengali | bn | 392,702 | 5,010 | 2,490 |
+Gujarati | gu |  392,702 | 5,010 | 2,490 |
+Hindi | hi | 392,702 | 5,010 | 2,490 |
+Kannada | kn |  392,702 | 5,010 | 2,490 |
+Malayalam | ml |392,702  | 5,010 | 2,490 |
+Marathi | mr |392,702 | 5,010 | 2,490 |
+Oriya | or | 392,702 | 5,010 | 2,490 |
+Punjabi | pa | 392,702 | 5,010 | 2,490 |
+Tamil | ta | 392,702 | 5,010 | 2,490 |
+Telugu | te | 392,702 | 5,010 | 2,490 |
+
+<!-- The dataset split remains same across all languages. -->
+
+## Dataset usage
+
+Code snippet for using the dataset using datasets library.
+
+```python
+from datasets import load_dataset
+
+dataset = load_dataset("Divyanshu/indicxnli")
+```
+
+## Dataset Creation
+
+Machine translation of XNLI english dataset to 11 listed Indic Languages.
+
+### Curation Rationale
+
+[More information needed]
+
+### Source Data
+
+[XNLI dataset](https://cims.nyu.edu/~sbowman/xnli/)
+
+#### Initial Data Collection and Normalization
+
+[Detailed in the paper](https://arxiv.org/abs/2304.13005)
+
+#### Who are the source language producers?
+
+[Detailed in the paper](https://arxiv.org/abs/2304.13005)
+
+#### Human Verification Process
+
+[Detailed in the paper](https://arxiv.org/abs/2304.13005)
+
+## Considerations for Using the Data
+
+### Social Impact of Dataset
+
+[Detailed in the paper](https://arxiv.org/abs/2304.13005)
+
+### Discussion of Biases
+
+[Detailed in the paper](https://arxiv.org/abs/2304.13005)
+
+### Other Known Limitations
+
+[Detailed in the paper](https://arxiv.org/abs/2304.13005)
+
+### Dataset Curators
+
+Divyanshu Aggarwal, Vivek Gupta, Anoop Kunchukuttan
+
+### Licensing Information
+
+Contents of this repository are restricted to only non-commercial research purposes under the [Creative Commons Attribution-NonCommercial 4.0 International License (CC BY-NC 4.0)](https://creativecommons.org/licenses/by-nc/4.0/). Copyright of the dataset contents belongs to the original copyright holders.
+
+### Citation Information
+
+If you use any of the datasets, models or code modules, please cite the following paper:
+
+```
+@misc{https://doi.org/10.48550/arxiv.2204.08776,
+  doi = {10.48550/ARXIV.2204.08776},
+  
+  url = {https://arxiv.org/abs/2304.13005},
+  
+  author = {Aggarwal, Divyanshu and Gupta, Vivek and Kunchukuttan, Anoop},
+  
+  keywords = {Computation and Language (cs.CL), Artificial Intelligence (cs.AI), FOS: Computer and information sciences, FOS: Computer and information sciences},
+  
+  title = {IE-SemParse: Evaluating Multilingual Inference for Indian Languages}, 
+  
+  publisher = {arXiv},
+  
+  year = {2022},
+  
+  copyright = {Creative Commons Attribution 4.0 International}
+}
+```
+
+<!-- ### Contributions -->

.history/README_20230707233734.md

@@ -0,0 +1,214 @@
+---
+annotations_creators:
+- machine-generated
+language_creators:
+- machine-generated
+language:
+- as
+- bn
+- gu
+- hi
+- kn
+- ml
+- mr
+- or
+- pa
+- ta
+- te
+license:
+- cc0-1.0
+multilinguality:
+- multilingual
+pretty_name: IE-SemParse
+size_categories:
+- 1M<n<10M
+source_datasets:
+- original
+task_categories:
+- text2text
+task_ids:
+- Semantic-Parsing
+---
+
+# Dataset Card for "IE-SemParse"
+
+## Table of Contents
+
+- [Dataset Card for "IE-SemParse"](#dataset-card-for-ie-semparse)
+  - [Table of Contents](#table-of-contents)
+  - [Dataset Description](#dataset-description)
+    - [Dataset Summary](#dataset-summary)
+    - [Supported Tasks and Leaderboards](#supported-tasks-and-leaderboards)
+    - [Languages](#languages)
+    - [Data Splits](#data-splits)
+  - [Dataset usage](#dataset-usage)
+  - [Dataset Creation](#dataset-creation)
+    - [Curation Rationale](#curation-rationale)
+    - [Source Data](#source-data)
+      - [Initial Data Collection and Normalization](#initial-data-collection-and-normalization)
+      - [Who are the source language producers?](#who-are-the-source-language-producers)
+      - [Human Verification Process](#human-verification-process)
+  - [Considerations for Using the Data](#considerations-for-using-the-data)
+    - [Social Impact of Dataset](#social-impact-of-dataset)
+    - [Discussion of Biases](#discussion-of-biases)
+    - [Other Known Limitations](#other-known-limitations)
+    - [Dataset Curators](#dataset-curators)
+    - [Licensing Information](#licensing-information)
+    - [Citation Information](#citation-information)
+
+## Dataset Description
+
+- **Homepage:** <https://github.com/divyanshuaggarwal/IE-SemParse>
+- **Paper:** [Evaluating Inter-Bilingual Semantic Parsing for Indian Languages](https://arxiv.org/abs/2304.13005)
+- **Point of Contact:** [Divyanshu Aggarwal](mailto:[email protected])
+
+### Dataset Summary
+
+IE-SemParse is an InterBilingual Semantic Parsing Dataset for eleven major Indic languages that includes
+Assamese (‘as’), Gujarat (‘gu’), Kannada (‘kn’),
+Malayalam (‘ml’), Marathi (‘mr’), Odia (‘or’),
+Punjabi (‘pa’), Tamil (‘ta’), Telugu (‘te’), Hindi
+(‘hi’), and Bengali (‘bn’).
+
+### Supported Tasks and Leaderboards
+
+**Tasks:** Natural Language Inference
+
+**Leaderboards:** Currently there is no Leaderboard for this dataset.
+
+### Languages
+
+- `Assamese (as)`
+- `Bengali (bn)`
+- `Gujarati (gu)`
+- `Kannada (kn)`
+- `Hindi (hi)`
+- `Malayalam (ml)`
+- `Marathi (mr)`
+- `Oriya (or)`
+- `Punjabi (pa)`
+- `Tamil (ta)`
+- `Telugu (te)`
+
+
+
+
+### Data Splits
+
+<!-- Below is the dataset split given for `hi` dataset.
+
+```python
+DatasetDict({
+    train: Dataset({
+        features: ['premise', 'hypothesis', 'label'],
+        num_rows: 392702
+    })
+    test: Dataset({
+        features: ['premise', 'hypothesis', 'label'],
+        num_rows: 5010
+    })
+    validation: Dataset({
+        features: ['premise', 'hypothesis', 'label'],
+        num_rows: 2490
+    })
+})
+
+``` -->
+
+Language      | ISO 639-1 Code |Train | Dev | Test |
+--------------|----------------|-------|-----|------|
+Assamese | as | 392,702 | 5,010 | 2,490 |
+Bengali | bn | 392,702 | 5,010 | 2,490 |
+Gujarati | gu |  392,702 | 5,010 | 2,490 |
+Hindi | hi | 392,702 | 5,010 | 2,490 |
+Kannada | kn |  392,702 | 5,010 | 2,490 |
+Malayalam | ml |392,702  | 5,010 | 2,490 |
+Marathi | mr |392,702 | 5,010 | 2,490 |
+Oriya | or | 392,702 | 5,010 | 2,490 |
+Punjabi | pa | 392,702 | 5,010 | 2,490 |
+Tamil | ta | 392,702 | 5,010 | 2,490 |
+Telugu | te | 392,702 | 5,010 | 2,490 |
+
+<!-- The dataset split remains same across all languages. -->
+
+## Dataset usage
+
+Code snippet for using the dataset using datasets library.
+
+```python
+from datasets import load_dataset
+
+dataset = load_dataset("Divyanshu/indicxnli")
+```
+
+## Dataset Creation
+
+Machine translation of XNLI english dataset to 11 listed Indic Languages.
+
+### Curation Rationale
+
+[More information needed]
+
+### Source Data
+
+[XNLI dataset](https://cims.nyu.edu/~sbowman/xnli/)
+
+#### Initial Data Collection and Normalization
+
+[Detailed in the paper](https://arxiv.org/abs/2304.13005)
+
+#### Who are the source language producers?
+
+[Detailed in the paper](https://arxiv.org/abs/2304.13005)
+
+#### Human Verification Process
+
+[Detailed in the paper](https://arxiv.org/abs/2304.13005)
+
+## Considerations for Using the Data
+
+### Social Impact of Dataset
+
+[Detailed in the paper](https://arxiv.org/abs/2304.13005)
+
+### Discussion of Biases
+
+[Detailed in the paper](https://arxiv.org/abs/2304.13005)
+
+### Other Known Limitations
+
+[Detailed in the paper](https://arxiv.org/abs/2304.13005)
+
+### Dataset Curators
+
+Divyanshu Aggarwal, Vivek Gupta, Anoop Kunchukuttan
+
+### Licensing Information
+
+Contents of this repository are restricted to only non-commercial research purposes under the [Creative Commons Attribution-NonCommercial 4.0 International License (CC BY-NC 4.0)](https://creativecommons.org/licenses/by-nc/4.0/). Copyright of the dataset contents belongs to the original copyright holders.
+
+### Citation Information
+
+If you use any of the datasets, models or code modules, please cite the following paper:
+
+```
+@misc{https://doi.org/10.48550/arxiv.2204.08776,
+  doi = {10.48550/ARXIV.2204.08776},
+  
+  url = {https://arxiv.org/abs/2304.13005},
+  
+  author = {Aggarwal, Divyanshu and Gupta, Vivek and Kunchukuttan, Anoop},
+  
+  keywords = {Computation and Language (cs.CL), Artificial Intelligence (cs.AI), FOS: Computer and information sciences, FOS: Computer and information sciences},
+  
+  title = {IE-SemParse: Evaluating Multilingual Inference for Indian Languages}, 
+  
+  publisher = {arXiv},
+  
+  year = {2022},
+  
+  copyright = {Creative Commons Attribution 4.0 International}
+}
+```
+
+<!-- ### Contributions -->

.history/README_20230707233737.md

@@ -0,0 +1,214 @@
+---
+annotations_creators:
+- machine-generated
+language_creators:
+- machine-generated
+language:
+- as
+- bn
+- gu
+- hi
+- kn
+- ml
+- mr
+- or
+- pa
+- ta
+- te
+license:
+- cc0-1.0
+multilinguality:
+- multilingual
+pretty_name: IE-SemParse
+size_categories:
+- 1M<n<10M
+source_datasets:
+- original
+task_categories:
+- text2text
+task_ids:
+- Semantic-Parsing
+---
+
+# Dataset Card for "IE-SemParse"
+
+## Table of Contents
+
+- [Dataset Card for "IE-SemParse"](#dataset-card-for-ie-semparse)
+  - [Table of Contents](#table-of-contents)
+  - [Dataset Description](#dataset-description)
+    - [Dataset Summary](#dataset-summary)
+    - [Supported Tasks and Leaderboards](#supported-tasks-and-leaderboards)
+    - [Languages](#languages)
+    - [Data Splits](#data-splits)
+  - [Dataset usage](#dataset-usage)
+  - [Dataset Creation](#dataset-creation)
+    - [Curation Rationale](#curation-rationale)
+    - [Source Data](#source-data)
+      - [Initial Data Collection and Normalization](#initial-data-collection-and-normalization)
+      - [Who are the source language producers?](#who-are-the-source-language-producers)
+      - [Human Verification Process](#human-verification-process)
+  - [Considerations for Using the Data](#considerations-for-using-the-data)
+    - [Social Impact of Dataset](#social-impact-of-dataset)
+    - [Discussion of Biases](#discussion-of-biases)
+    - [Other Known Limitations](#other-known-limitations)
+    - [Dataset Curators](#dataset-curators)
+    - [Licensing Information](#licensing-information)
+    - [Citation Information](#citation-information)
+
+## Dataset Description
+
+- **Homepage:** <https://github.com/divyanshuaggarwal/IE-SemParse>
+- **Paper:** [Evaluating Inter-Bilingual Semantic Parsing for Indian Languages](https://arxiv.org/abs/2304.13005)
+- **Point of Contact:** [Divyanshu Aggarwal](mailto:[email protected])
+
+### Dataset Summary
+
+IE-SemParse is an InterBilingual Semantic Parsing Dataset for eleven major Indic languages that includes
+Assamese (‘as’), Gujarat (‘gu’), Kannada (‘kn’),
+Malayalam (‘ml’), Marathi (‘mr’), Odia (‘or’),
+Punjabi (‘pa’), Tamil (‘ta’), Telugu (‘te’), Hindi
+(‘hi’), and Bengali (‘bn’).
+
+### Supported Tasks and Leaderboards
+
+**Tasks:** Natural Language Inference
+
+**Leaderboards:** Currently there is no Leaderboard for this dataset.
+
+### Languages
+
+- `Assamese (as)`
+- `Bengali (bn)`
+- `Gujarati (gu)`
+- `Kannada (kn)`
+- `Hindi (hi)`
+- `Malayalam (ml)`
+- `Marathi (mr)`
+- `Oriya (or)`
+- `Punjabi (pa)`
+- `Tamil (ta)`
+- `Telugu (te)`
+
+...
+
+
+### Data Splits
+
+<!-- Below is the dataset split given for `hi` dataset.
+
+```python
+DatasetDict({
+    train: Dataset({
+        features: ['premise', 'hypothesis', 'label'],
+        num_rows: 392702
+    })
+    test: Dataset({
+        features: ['premise', 'hypothesis', 'label'],
+        num_rows: 5010
+    })
+    validation: Dataset({
+        features: ['premise', 'hypothesis', 'label'],
+        num_rows: 2490
+    })
+})
+
+``` -->
+
+Language      | ISO 639-1 Code |Train | Dev | Test |
+--------------|----------------|-------|-----|------|
+Assamese | as | 392,702 | 5,010 | 2,490 |
+Bengali | bn | 392,702 | 5,010 | 2,490 |
+Gujarati | gu |  392,702 | 5,010 | 2,490 |
+Hindi | hi | 392,702 | 5,010 | 2,490 |
+Kannada | kn |  392,702 | 5,010 | 2,490 |
+Malayalam | ml |392,702  | 5,010 | 2,490 |
+Marathi | mr |392,702 | 5,010 | 2,490 |
+Oriya | or | 392,702 | 5,010 | 2,490 |
+Punjabi | pa | 392,702 | 5,010 | 2,490 |
+Tamil | ta | 392,702 | 5,010 | 2,490 |
+Telugu | te | 392,702 | 5,010 | 2,490 |
+
+<!-- The dataset split remains same across all languages. -->
+
+## Dataset usage
+
+Code snippet for using the dataset using datasets library.
+
+```python
+from datasets import load_dataset
+
+dataset = load_dataset("Divyanshu/indicxnli")
+```
+
+## Dataset Creation
+
+Machine translation of XNLI english dataset to 11 listed Indic Languages.
+
+### Curation Rationale
+
+[More information needed]
+
+### Source Data
+
+[XNLI dataset](https://cims.nyu.edu/~sbowman/xnli/)
+
+#### Initial Data Collection and Normalization
+
+[Detailed in the paper](https://arxiv.org/abs/2304.13005)
+
+#### Who are the source language producers?
+
+[Detailed in the paper](https://arxiv.org/abs/2304.13005)
+
+#### Human Verification Process
+
+[Detailed in the paper](https://arxiv.org/abs/2304.13005)
+
+## Considerations for Using the Data
+
+### Social Impact of Dataset
+
+[Detailed in the paper](https://arxiv.org/abs/2304.13005)
+
+### Discussion of Biases
+
+[Detailed in the paper](https://arxiv.org/abs/2304.13005)
+
+### Other Known Limitations
+
+[Detailed in the paper](https://arxiv.org/abs/2304.13005)
+
+### Dataset Curators
+
+Divyanshu Aggarwal, Vivek Gupta, Anoop Kunchukuttan
+
+### Licensing Information
+
+Contents of this repository are restricted to only non-commercial research purposes under the [Creative Commons Attribution-NonCommercial 4.0 International License (CC BY-NC 4.0)](https://creativecommons.org/licenses/by-nc/4.0/). Copyright of the dataset contents belongs to the original copyright holders.
+
+### Citation Information
+
+If you use any of the datasets, models or code modules, please cite the following paper:
+
+```
+@misc{https://doi.org/10.48550/arxiv.2204.08776,
+  doi = {10.48550/ARXIV.2204.08776},
+  
+  url = {https://arxiv.org/abs/2304.13005},
+  
+  author = {Aggarwal, Divyanshu and Gupta, Vivek and Kunchukuttan, Anoop},
+  
+  keywords = {Computation and Language (cs.CL), Artificial Intelligence (cs.AI), FOS: Computer and information sciences, FOS: Computer and information sciences},
+  
+  title = {IE-SemParse: Evaluating Multilingual Inference for Indian Languages}, 
+  
+  publisher = {arXiv},
+  
+  year = {2022},
+  
+  copyright = {Creative Commons Attribution 4.0 International}
+}
+```
+
+<!-- ### Contributions -->

.history/README_20230707233747.md

@@ -0,0 +1,214 @@
+---
+annotations_creators:
+- machine-generated
+language_creators:
+- machine-generated
+language:
+- as
+- bn
+- gu
+- hi
+- kn
+- ml
+- mr
+- or
+- pa
+- ta
+- te
+license:
+- cc0-1.0
+multilinguality:
+- multilingual
+pretty_name: IE-SemParse
+size_categories:
+- 1M<n<10M
+source_datasets:
+- original
+task_categories:
+- text2text
+task_ids:
+- Semantic-Parsing
+---
+
+# Dataset Card for "IE-SemParse"
+
+## Table of Contents
+
+- [Dataset Card for "IE-SemParse"](#dataset-card-for-ie-semparse)
+  - [Table of Contents](#table-of-contents)
+  - [Dataset Description](#dataset-description)
+    - [Dataset Summary](#dataset-summary)
+    - [Supported Tasks and Leaderboards](#supported-tasks-and-leaderboards)
+    - [Languages](#languages)
+    - [Data Splits](#data-splits)
+  - [Dataset usage](#dataset-usage)
+  - [Dataset Creation](#dataset-creation)
+    - [Curation Rationale](#curation-rationale)
+    - [Source Data](#source-data)
+      - [Initial Data Collection and Normalization](#initial-data-collection-and-normalization)
+      - [Who are the source language producers?](#who-are-the-source-language-producers)
+      - [Human Verification Process](#human-verification-process)
+  - [Considerations for Using the Data](#considerations-for-using-the-data)
+    - [Social Impact of Dataset](#social-impact-of-dataset)
+    - [Discussion of Biases](#discussion-of-biases)
+    - [Other Known Limitations](#other-known-limitations)
+    - [Dataset Curators](#dataset-curators)
+    - [Licensing Information](#licensing-information)
+    - [Citation Information](#citation-information)
+
+## Dataset Description
+
+- **Homepage:** <https://github.com/divyanshuaggarwal/IE-SemParse>
+- **Paper:** [Evaluating Inter-Bilingual Semantic Parsing for Indian Languages](https://arxiv.org/abs/2304.13005)
+- **Point of Contact:** [Divyanshu Aggarwal](mailto:[email protected])
+
+### Dataset Summary
+
+IE-SemParse is an InterBilingual Semantic Parsing Dataset for eleven major Indic languages that includes
+Assamese (‘as’), Gujarat (‘gu’), Kannada (‘kn’),
+Malayalam (‘ml’), Marathi (‘mr’), Odia (‘or’),
+Punjabi (‘pa’), Tamil (‘ta’), Telugu (‘te’), Hindi
+(‘hi’), and Bengali (‘bn’).
+
+### Supported Tasks and Leaderboards
+
+**Tasks:** Natural Language Inference
+
+**Leaderboards:** Currently there is no Leaderboard for this dataset.
+
+### Languages
+
+- `Assamese (as)`
+- `Bengali (bn)`
+- `Gujarati (gu)`
+- `Kannada (kn)`
+- `Hindi (hi)`
+- `Malayalam (ml)`
+- `Marathi (mr)`
+- `Oriya (or)`
+- `Punjabi (pa)`
+- `Tamil (ta)`
+- `Telugu (te)`
+
+...
+
+
+### Data Splits
+
+<!-- Below is the dataset split given for `hi` dataset.
+
+```python
+DatasetDict({
+    train: Dataset({
+        features: ['utterance', 'hypothesis', 'label'],
+        num_rows: 392702
+    })
+    test: Dataset({
+        features: ['premise', 'hypothesis', 'label'],
+        num_rows: 5010
+    })
+    validation: Dataset({
+        features: ['premise', 'hypothesis', 'label'],
+        num_rows: 2490
+    })
+})
+
+``` -->
+
+Language      | ISO 639-1 Code |Train | Dev | Test |
+--------------|----------------|-------|-----|------|
+Assamese | as | 392,702 | 5,010 | 2,490 |
+Bengali | bn | 392,702 | 5,010 | 2,490 |
+Gujarati | gu |  392,702 | 5,010 | 2,490 |
+Hindi | hi | 392,702 | 5,010 | 2,490 |
+Kannada | kn |  392,702 | 5,010 | 2,490 |
+Malayalam | ml |392,702  | 5,010 | 2,490 |
+Marathi | mr |392,702 | 5,010 | 2,490 |
+Oriya | or | 392,702 | 5,010 | 2,490 |
+Punjabi | pa | 392,702 | 5,010 | 2,490 |
+Tamil | ta | 392,702 | 5,010 | 2,490 |
+Telugu | te | 392,702 | 5,010 | 2,490 |
+
+<!-- The dataset split remains same across all languages. -->
+
+## Dataset usage
+
+Code snippet for using the dataset using datasets library.
+
+```python
+from datasets import load_dataset
+
+dataset = load_dataset("Divyanshu/indicxnli")
+```
+
+## Dataset Creation
+
+Machine translation of XNLI english dataset to 11 listed Indic Languages.
+
+### Curation Rationale
+
+[More information needed]
+
+### Source Data
+
+[XNLI dataset](https://cims.nyu.edu/~sbowman/xnli/)
+
+#### Initial Data Collection and Normalization
+
+[Detailed in the paper](https://arxiv.org/abs/2304.13005)
+
+#### Who are the source language producers?
+
+[Detailed in the paper](https://arxiv.org/abs/2304.13005)
+
+#### Human Verification Process
+
+[Detailed in the paper](https://arxiv.org/abs/2304.13005)
+
+## Considerations for Using the Data
+
+### Social Impact of Dataset
+
+[Detailed in the paper](https://arxiv.org/abs/2304.13005)
+
+### Discussion of Biases
+
+[Detailed in the paper](https://arxiv.org/abs/2304.13005)
+
+### Other Known Limitations
+
+[Detailed in the paper](https://arxiv.org/abs/2304.13005)
+
+### Dataset Curators
+
+Divyanshu Aggarwal, Vivek Gupta, Anoop Kunchukuttan
+
+### Licensing Information
+
+Contents of this repository are restricted to only non-commercial research purposes under the [Creative Commons Attribution-NonCommercial 4.0 International License (CC BY-NC 4.0)](https://creativecommons.org/licenses/by-nc/4.0/). Copyright of the dataset contents belongs to the original copyright holders.
+
+### Citation Information
+
+If you use any of the datasets, models or code modules, please cite the following paper:
+
+```
+@misc{https://doi.org/10.48550/arxiv.2204.08776,
+  doi = {10.48550/ARXIV.2204.08776},
+  
+  url = {https://arxiv.org/abs/2304.13005},
+  
+  author = {Aggarwal, Divyanshu and Gupta, Vivek and Kunchukuttan, Anoop},
+  
+  keywords = {Computation and Language (cs.CL), Artificial Intelligence (cs.AI), FOS: Computer and information sciences, FOS: Computer and information sciences},
+  
+  title = {IE-SemParse: Evaluating Multilingual Inference for Indian Languages}, 
+  
+  publisher = {arXiv},
+  
+  year = {2022},
+  
+  copyright = {Creative Commons Attribution 4.0 International}
+}
+```
+
+<!-- ### Contributions -->

.history/README_20230707233751.md

@@ -0,0 +1,214 @@
+---
+annotations_creators:
+- machine-generated
+language_creators:
+- machine-generated
+language:
+- as
+- bn
+- gu
+- hi
+- kn
+- ml
+- mr
+- or
+- pa
+- ta
+- te
+license:
+- cc0-1.0
+multilinguality:
+- multilingual
+pretty_name: IE-SemParse
+size_categories:
+- 1M<n<10M
+source_datasets:
+- original
+task_categories:
+- text2text
+task_ids:
+- Semantic-Parsing
+---
+
+# Dataset Card for "IE-SemParse"
+
+## Table of Contents
+
+- [Dataset Card for "IE-SemParse"](#dataset-card-for-ie-semparse)
+  - [Table of Contents](#table-of-contents)
+  - [Dataset Description](#dataset-description)
+    - [Dataset Summary](#dataset-summary)
+    - [Supported Tasks and Leaderboards](#supported-tasks-and-leaderboards)
+    - [Languages](#languages)
+    - [Data Splits](#data-splits)
+  - [Dataset usage](#dataset-usage)
+  - [Dataset Creation](#dataset-creation)
+    - [Curation Rationale](#curation-rationale)
+    - [Source Data](#source-data)
+      - [Initial Data Collection and Normalization](#initial-data-collection-and-normalization)
+      - [Who are the source language producers?](#who-are-the-source-language-producers)
+      - [Human Verification Process](#human-verification-process)
+  - [Considerations for Using the Data](#considerations-for-using-the-data)
+    - [Social Impact of Dataset](#social-impact-of-dataset)
+    - [Discussion of Biases](#discussion-of-biases)
+    - [Other Known Limitations](#other-known-limitations)
+    - [Dataset Curators](#dataset-curators)
+    - [Licensing Information](#licensing-information)
+    - [Citation Information](#citation-information)
+
+## Dataset Description
+
+- **Homepage:** <https://github.com/divyanshuaggarwal/IE-SemParse>
+- **Paper:** [Evaluating Inter-Bilingual Semantic Parsing for Indian Languages](https://arxiv.org/abs/2304.13005)
+- **Point of Contact:** [Divyanshu Aggarwal](mailto:[email protected])
+
+### Dataset Summary
+
+IE-SemParse is an InterBilingual Semantic Parsing Dataset for eleven major Indic languages that includes
+Assamese (‘as’), Gujarat (‘gu’), Kannada (‘kn’),
+Malayalam (‘ml’), Marathi (‘mr’), Odia (‘or’),
+Punjabi (‘pa’), Tamil (‘ta’), Telugu (‘te’), Hindi
+(‘hi’), and Bengali (‘bn’).
+
+### Supported Tasks and Leaderboards
+
+**Tasks:** Natural Language Inference
+
+**Leaderboards:** Currently there is no Leaderboard for this dataset.
+
+### Languages
+
+- `Assamese (as)`
+- `Bengali (bn)`
+- `Gujarati (gu)`
+- `Kannada (kn)`
+- `Hindi (hi)`
+- `Malayalam (ml)`
+- `Marathi (mr)`
+- `Oriya (or)`
+- `Punjabi (pa)`
+- `Tamil (ta)`
+- `Telugu (te)`
+
+...
+
+
+### Data Splits
+
+<!-- Below is the dataset split given for `hi` dataset.
+
+```python
+DatasetDict({
+    train: Dataset({
+        features: ['utterance', 'logical form', 'label'],
+        num_rows: 392702
+    })
+    test: Dataset({
+        features: ['premise', 'hypothesis', 'label'],
+        num_rows: 5010
+    })
+    validation: Dataset({
+        features: ['premise', 'hypothesis', 'label'],
+        num_rows: 2490
+    })
+})
+
+``` -->
+
+Language      | ISO 639-1 Code |Train | Dev | Test |
+--------------|----------------|-------|-----|------|
+Assamese | as | 392,702 | 5,010 | 2,490 |
+Bengali | bn | 392,702 | 5,010 | 2,490 |
+Gujarati | gu |  392,702 | 5,010 | 2,490 |
+Hindi | hi | 392,702 | 5,010 | 2,490 |
+Kannada | kn |  392,702 | 5,010 | 2,490 |
+Malayalam | ml |392,702  | 5,010 | 2,490 |
+Marathi | mr |392,702 | 5,010 | 2,490 |
+Oriya | or | 392,702 | 5,010 | 2,490 |
+Punjabi | pa | 392,702 | 5,010 | 2,490 |
+Tamil | ta | 392,702 | 5,010 | 2,490 |
+Telugu | te | 392,702 | 5,010 | 2,490 |
+
+<!-- The dataset split remains same across all languages. -->
+
+## Dataset usage
+
+Code snippet for using the dataset using datasets library.
+
+```python
+from datasets import load_dataset
+
+dataset = load_dataset("Divyanshu/indicxnli")
+```
+
+## Dataset Creation
+
+Machine translation of XNLI english dataset to 11 listed Indic Languages.
+
+### Curation Rationale
+
+[More information needed]
+
+### Source Data
+
+[XNLI dataset](https://cims.nyu.edu/~sbowman/xnli/)
+
+#### Initial Data Collection and Normalization
+
+[Detailed in the paper](https://arxiv.org/abs/2304.13005)
+
+#### Who are the source language producers?
+
+[Detailed in the paper](https://arxiv.org/abs/2304.13005)
+
+#### Human Verification Process
+
+[Detailed in the paper](https://arxiv.org/abs/2304.13005)
+
+## Considerations for Using the Data
+
+### Social Impact of Dataset
+
+[Detailed in the paper](https://arxiv.org/abs/2304.13005)
+
+### Discussion of Biases
+
+[Detailed in the paper](https://arxiv.org/abs/2304.13005)
+
+### Other Known Limitations
+
+[Detailed in the paper](https://arxiv.org/abs/2304.13005)
+
+### Dataset Curators
+
+Divyanshu Aggarwal, Vivek Gupta, Anoop Kunchukuttan
+
+### Licensing Information
+
+Contents of this repository are restricted to only non-commercial research purposes under the [Creative Commons Attribution-NonCommercial 4.0 International License (CC BY-NC 4.0)](https://creativecommons.org/licenses/by-nc/4.0/). Copyright of the dataset contents belongs to the original copyright holders.
+
+### Citation Information
+
+If you use any of the datasets, models or code modules, please cite the following paper:
+
+```
+@misc{https://doi.org/10.48550/arxiv.2204.08776,
+  doi = {10.48550/ARXIV.2204.08776},
+  
+  url = {https://arxiv.org/abs/2304.13005},
+  
+  author = {Aggarwal, Divyanshu and Gupta, Vivek and Kunchukuttan, Anoop},
+  
+  keywords = {Computation and Language (cs.CL), Artificial Intelligence (cs.AI), FOS: Computer and information sciences, FOS: Computer and information sciences},
+  
+  title = {IE-SemParse: Evaluating Multilingual Inference for Indian Languages}, 
+  
+  publisher = {arXiv},
+  
+  year = {2022},
+  
+  copyright = {Creative Commons Attribution 4.0 International}
+}
+```
+
+<!-- ### Contributions -->

.history/README_20230707233753.md

@@ -0,0 +1,214 @@
+---
+annotations_creators:
+- machine-generated
+language_creators:
+- machine-generated
+language:
+- as
+- bn
+- gu
+- hi
+- kn
+- ml
+- mr
+- or
+- pa
+- ta
+- te
+license:
+- cc0-1.0
+multilinguality:
+- multilingual
+pretty_name: IE-SemParse
+size_categories:
+- 1M<n<10M
+source_datasets:
+- original
+task_categories:
+- text2text
+task_ids:
+- Semantic-Parsing
+---
+
+# Dataset Card for "IE-SemParse"
+
+## Table of Contents
+
+- [Dataset Card for "IE-SemParse"](#dataset-card-for-ie-semparse)
+  - [Table of Contents](#table-of-contents)
+  - [Dataset Description](#dataset-description)
+    - [Dataset Summary](#dataset-summary)
+    - [Supported Tasks and Leaderboards](#supported-tasks-and-leaderboards)
+    - [Languages](#languages)
+    - [Data Splits](#data-splits)
+  - [Dataset usage](#dataset-usage)
+  - [Dataset Creation](#dataset-creation)
+    - [Curation Rationale](#curation-rationale)
+    - [Source Data](#source-data)
+      - [Initial Data Collection and Normalization](#initial-data-collection-and-normalization)
+      - [Who are the source language producers?](#who-are-the-source-language-producers)
+      - [Human Verification Process](#human-verification-process)
+  - [Considerations for Using the Data](#considerations-for-using-the-data)
+    - [Social Impact of Dataset](#social-impact-of-dataset)
+    - [Discussion of Biases](#discussion-of-biases)
+    - [Other Known Limitations](#other-known-limitations)
+    - [Dataset Curators](#dataset-curators)
+    - [Licensing Information](#licensing-information)
+    - [Citation Information](#citation-information)
+
+## Dataset Description
+
+- **Homepage:** <https://github.com/divyanshuaggarwal/IE-SemParse>
+- **Paper:** [Evaluating Inter-Bilingual Semantic Parsing for Indian Languages](https://arxiv.org/abs/2304.13005)
+- **Point of Contact:** [Divyanshu Aggarwal](mailto:[email protected])
+
+### Dataset Summary
+
+IE-SemParse is an InterBilingual Semantic Parsing Dataset for eleven major Indic languages that includes
+Assamese (‘as’), Gujarat (‘gu’), Kannada (‘kn’),
+Malayalam (‘ml’), Marathi (‘mr’), Odia (‘or’),
+Punjabi (‘pa’), Tamil (‘ta’), Telugu (‘te’), Hindi
+(‘hi’), and Bengali (‘bn’).
+
+### Supported Tasks and Leaderboards
+
+**Tasks:** Natural Language Inference
+
+**Leaderboards:** Currently there is no Leaderboard for this dataset.
+
+### Languages
+
+- `Assamese (as)`
+- `Bengali (bn)`
+- `Gujarati (gu)`
+- `Kannada (kn)`
+- `Hindi (hi)`
+- `Malayalam (ml)`
+- `Marathi (mr)`
+- `Oriya (or)`
+- `Punjabi (pa)`
+- `Tamil (ta)`
+- `Telugu (te)`
+
+...
+
+
+### Data Splits
+
+<!-- Below is the dataset split given for `hi` dataset.
+
+```python
+DatasetDict({
+    train: Dataset({
+        features: ['utterance', 'logical form', 'intent'],
+        num_rows: 392702
+    })
+    test: Dataset({
+        features: ['premise', 'hypothesis', 'label'],
+        num_rows: 5010
+    })
+    validation: Dataset({
+        features: ['premise', 'hypothesis', 'label'],
+        num_rows: 2490
+    })
+})
+
+``` -->
+
+Language      | ISO 639-1 Code |Train | Dev | Test |
+--------------|----------------|-------|-----|------|
+Assamese | as | 392,702 | 5,010 | 2,490 |
+Bengali | bn | 392,702 | 5,010 | 2,490 |
+Gujarati | gu |  392,702 | 5,010 | 2,490 |
+Hindi | hi | 392,702 | 5,010 | 2,490 |
+Kannada | kn |  392,702 | 5,010 | 2,490 |
+Malayalam | ml |392,702  | 5,010 | 2,490 |
+Marathi | mr |392,702 | 5,010 | 2,490 |
+Oriya | or | 392,702 | 5,010 | 2,490 |
+Punjabi | pa | 392,702 | 5,010 | 2,490 |
+Tamil | ta | 392,702 | 5,010 | 2,490 |
+Telugu | te | 392,702 | 5,010 | 2,490 |
+
+<!-- The dataset split remains same across all languages. -->
+
+## Dataset usage
+
+Code snippet for using the dataset using datasets library.
+
+```python
+from datasets import load_dataset
+
+dataset = load_dataset("Divyanshu/indicxnli")
+```
+
+## Dataset Creation
+
+Machine translation of XNLI english dataset to 11 listed Indic Languages.
+
+### Curation Rationale
+
+[More information needed]
+
+### Source Data
+
+[XNLI dataset](https://cims.nyu.edu/~sbowman/xnli/)
+
+#### Initial Data Collection and Normalization
+
+[Detailed in the paper](https://arxiv.org/abs/2304.13005)
+
+#### Who are the source language producers?
+
+[Detailed in the paper](https://arxiv.org/abs/2304.13005)
+
+#### Human Verification Process
+
+[Detailed in the paper](https://arxiv.org/abs/2304.13005)
+
+## Considerations for Using the Data
+
+### Social Impact of Dataset
+
+[Detailed in the paper](https://arxiv.org/abs/2304.13005)
+
+### Discussion of Biases
+
+[Detailed in the paper](https://arxiv.org/abs/2304.13005)
+
+### Other Known Limitations
+
+[Detailed in the paper](https://arxiv.org/abs/2304.13005)
+
+### Dataset Curators
+
+Divyanshu Aggarwal, Vivek Gupta, Anoop Kunchukuttan
+
+### Licensing Information
+
+Contents of this repository are restricted to only non-commercial research purposes under the [Creative Commons Attribution-NonCommercial 4.0 International License (CC BY-NC 4.0)](https://creativecommons.org/licenses/by-nc/4.0/). Copyright of the dataset contents belongs to the original copyright holders.
+
+### Citation Information
+
+If you use any of the datasets, models or code modules, please cite the following paper:
+
+```
+@misc{https://doi.org/10.48550/arxiv.2204.08776,
+  doi = {10.48550/ARXIV.2204.08776},
+  
+  url = {https://arxiv.org/abs/2304.13005},
+  
+  author = {Aggarwal, Divyanshu and Gupta, Vivek and Kunchukuttan, Anoop},
+  
+  keywords = {Computation and Language (cs.CL), Artificial Intelligence (cs.AI), FOS: Computer and information sciences, FOS: Computer and information sciences},
+  
+  title = {IE-SemParse: Evaluating Multilingual Inference for Indian Languages}, 
+  
+  publisher = {arXiv},
+  
+  year = {2022},
+  
+  copyright = {Creative Commons Attribution 4.0 International}
+}
+```
+
+<!-- ### Contributions -->

.history/README_20230707233759.md

@@ -0,0 +1,214 @@
+---
+annotations_creators:
+- machine-generated
+language_creators:
+- machine-generated
+language:
+- as
+- bn
+- gu
+- hi
+- kn
+- ml
+- mr
+- or
+- pa
+- ta
+- te
+license:
+- cc0-1.0
+multilinguality:
+- multilingual
+pretty_name: IE-SemParse
+size_categories:
+- 1M<n<10M
+source_datasets:
+- original
+task_categories:
+- text2text
+task_ids:
+- Semantic-Parsing
+---
+
+# Dataset Card for "IE-SemParse"
+
+## Table of Contents
+
+- [Dataset Card for "IE-SemParse"](#dataset-card-for-ie-semparse)
+  - [Table of Contents](#table-of-contents)
+  - [Dataset Description](#dataset-description)
+    - [Dataset Summary](#dataset-summary)
+    - [Supported Tasks and Leaderboards](#supported-tasks-and-leaderboards)
+    - [Languages](#languages)
+    - [Data Splits](#data-splits)
+  - [Dataset usage](#dataset-usage)
+  - [Dataset Creation](#dataset-creation)
+    - [Curation Rationale](#curation-rationale)
+    - [Source Data](#source-data)
+      - [Initial Data Collection and Normalization](#initial-data-collection-and-normalization)
+      - [Who are the source language producers?](#who-are-the-source-language-producers)
+      - [Human Verification Process](#human-verification-process)
+  - [Considerations for Using the Data](#considerations-for-using-the-data)
+    - [Social Impact of Dataset](#social-impact-of-dataset)
+    - [Discussion of Biases](#discussion-of-biases)
+    - [Other Known Limitations](#other-known-limitations)
+    - [Dataset Curators](#dataset-curators)
+    - [Licensing Information](#licensing-information)
+    - [Citation Information](#citation-information)
+
+## Dataset Description
+
+- **Homepage:** <https://github.com/divyanshuaggarwal/IE-SemParse>
+- **Paper:** [Evaluating Inter-Bilingual Semantic Parsing for Indian Languages](https://arxiv.org/abs/2304.13005)
+- **Point of Contact:** [Divyanshu Aggarwal](mailto:[email protected])
+
+### Dataset Summary
+
+IE-SemParse is an InterBilingual Semantic Parsing Dataset for eleven major Indic languages that includes
+Assamese (‘as’), Gujarat (‘gu’), Kannada (‘kn’),
+Malayalam (‘ml’), Marathi (‘mr’), Odia (‘or’),
+Punjabi (‘pa’), Tamil (‘ta’), Telugu (‘te’), Hindi
+(‘hi’), and Bengali (‘bn’).
+
+### Supported Tasks and Leaderboards
+
+**Tasks:** Natural Language Inference
+
+**Leaderboards:** Currently there is no Leaderboard for this dataset.
+
+### Languages
+
+- `Assamese (as)`
+- `Bengali (bn)`
+- `Gujarati (gu)`
+- `Kannada (kn)`
+- `Hindi (hi)`
+- `Malayalam (ml)`
+- `Marathi (mr)`
+- `Oriya (or)`
+- `Punjabi (pa)`
+- `Tamil (ta)`
+- `Telugu (te)`
+
+...
+
+
+### Data Splits
+
+<!-- Below is the dataset split given for `hi` dataset.
+
+```python
+DatasetDict({
+    train: Dataset({
+        features: ['utterance', 'logical form', 'intent'],
+        num_rows: 392702
+    })
+    test: Dataset({
+        features: ['utterance', 'logical form', 'intent'],
+        num_rows: 5010
+    })
+    validation: Dataset({
+        features: ['premise', 'hypothesis', 'label'],
+        num_rows: 2490
+    })
+})
+
+``` -->
+
+Language      | ISO 639-1 Code |Train | Dev | Test |
+--------------|----------------|-------|-----|------|
+Assamese | as | 392,702 | 5,010 | 2,490 |
+Bengali | bn | 392,702 | 5,010 | 2,490 |
+Gujarati | gu |  392,702 | 5,010 | 2,490 |
+Hindi | hi | 392,702 | 5,010 | 2,490 |
+Kannada | kn |  392,702 | 5,010 | 2,490 |
+Malayalam | ml |392,702  | 5,010 | 2,490 |
+Marathi | mr |392,702 | 5,010 | 2,490 |
+Oriya | or | 392,702 | 5,010 | 2,490 |
+Punjabi | pa | 392,702 | 5,010 | 2,490 |
+Tamil | ta | 392,702 | 5,010 | 2,490 |
+Telugu | te | 392,702 | 5,010 | 2,490 |
+
+<!-- The dataset split remains same across all languages. -->
+
+## Dataset usage
+
+Code snippet for using the dataset using datasets library.
+
+```python
+from datasets import load_dataset
+
+dataset = load_dataset("Divyanshu/indicxnli")
+```
+
+## Dataset Creation
+
+Machine translation of XNLI english dataset to 11 listed Indic Languages.
+
+### Curation Rationale
+
+[More information needed]
+
+### Source Data
+
+[XNLI dataset](https://cims.nyu.edu/~sbowman/xnli/)
+
+#### Initial Data Collection and Normalization
+
+[Detailed in the paper](https://arxiv.org/abs/2304.13005)
+
+#### Who are the source language producers?
+
+[Detailed in the paper](https://arxiv.org/abs/2304.13005)
+
+#### Human Verification Process
+
+[Detailed in the paper](https://arxiv.org/abs/2304.13005)
+
+## Considerations for Using the Data
+
+### Social Impact of Dataset
+
+[Detailed in the paper](https://arxiv.org/abs/2304.13005)
+
+### Discussion of Biases
+
+[Detailed in the paper](https://arxiv.org/abs/2304.13005)
+
+### Other Known Limitations
+
+[Detailed in the paper](https://arxiv.org/abs/2304.13005)
+
+### Dataset Curators
+
+Divyanshu Aggarwal, Vivek Gupta, Anoop Kunchukuttan
+
+### Licensing Information
+
+Contents of this repository are restricted to only non-commercial research purposes under the [Creative Commons Attribution-NonCommercial 4.0 International License (CC BY-NC 4.0)](https://creativecommons.org/licenses/by-nc/4.0/). Copyright of the dataset contents belongs to the original copyright holders.
+
+### Citation Information
+
+If you use any of the datasets, models or code modules, please cite the following paper:
+
+```
+@misc{https://doi.org/10.48550/arxiv.2204.08776,
+  doi = {10.48550/ARXIV.2204.08776},
+  
+  url = {https://arxiv.org/abs/2304.13005},
+  
+  author = {Aggarwal, Divyanshu and Gupta, Vivek and Kunchukuttan, Anoop},
+  
+  keywords = {Computation and Language (cs.CL), Artificial Intelligence (cs.AI), FOS: Computer and information sciences, FOS: Computer and information sciences},
+  
+  title = {IE-SemParse: Evaluating Multilingual Inference for Indian Languages}, 
+  
+  publisher = {arXiv},
+  
+  year = {2022},
+  
+  copyright = {Creative Commons Attribution 4.0 International}
+}
+```
+
+<!-- ### Contributions -->

.history/README_20230707233801.md

@@ -0,0 +1,214 @@
+---
+annotations_creators:
+- machine-generated
+language_creators:
+- machine-generated
+language:
+- as
+- bn
+- gu
+- hi
+- kn
+- ml
+- mr
+- or
+- pa
+- ta
+- te
+license:
+- cc0-1.0
+multilinguality:
+- multilingual
+pretty_name: IE-SemParse
+size_categories:
+- 1M<n<10M
+source_datasets:
+- original
+task_categories:
+- text2text
+task_ids:
+- Semantic-Parsing
+---
+
+# Dataset Card for "IE-SemParse"
+
+## Table of Contents
+
+- [Dataset Card for "IE-SemParse"](#dataset-card-for-ie-semparse)
+  - [Table of Contents](#table-of-contents)
+  - [Dataset Description](#dataset-description)
+    - [Dataset Summary](#dataset-summary)
+    - [Supported Tasks and Leaderboards](#supported-tasks-and-leaderboards)
+    - [Languages](#languages)
+    - [Data Splits](#data-splits)
+  - [Dataset usage](#dataset-usage)
+  - [Dataset Creation](#dataset-creation)
+    - [Curation Rationale](#curation-rationale)
+    - [Source Data](#source-data)
+      - [Initial Data Collection and Normalization](#initial-data-collection-and-normalization)
+      - [Who are the source language producers?](#who-are-the-source-language-producers)
+      - [Human Verification Process](#human-verification-process)
+  - [Considerations for Using the Data](#considerations-for-using-the-data)
+    - [Social Impact of Dataset](#social-impact-of-dataset)
+    - [Discussion of Biases](#discussion-of-biases)
+    - [Other Known Limitations](#other-known-limitations)
+    - [Dataset Curators](#dataset-curators)
+    - [Licensing Information](#licensing-information)
+    - [Citation Information](#citation-information)
+
+## Dataset Description
+
+- **Homepage:** <https://github.com/divyanshuaggarwal/IE-SemParse>
+- **Paper:** [Evaluating Inter-Bilingual Semantic Parsing for Indian Languages](https://arxiv.org/abs/2304.13005)
+- **Point of Contact:** [Divyanshu Aggarwal](mailto:[email protected])
+
+### Dataset Summary
+
+IE-SemParse is an InterBilingual Semantic Parsing Dataset for eleven major Indic languages that includes
+Assamese (‘as’), Gujarat (‘gu’), Kannada (‘kn’),
+Malayalam (‘ml’), Marathi (‘mr’), Odia (‘or’),
+Punjabi (‘pa’), Tamil (‘ta’), Telugu (‘te’), Hindi
+(‘hi’), and Bengali (‘bn’).
+
+### Supported Tasks and Leaderboards
+
+**Tasks:** Natural Language Inference
+
+**Leaderboards:** Currently there is no Leaderboard for this dataset.
+
+### Languages
+
+- `Assamese (as)`
+- `Bengali (bn)`
+- `Gujarati (gu)`
+- `Kannada (kn)`
+- `Hindi (hi)`
+- `Malayalam (ml)`
+- `Marathi (mr)`
+- `Oriya (or)`
+- `Punjabi (pa)`
+- `Tamil (ta)`
+- `Telugu (te)`
+
+...
+
+
+### Data Splits
+
+<!-- Below is the dataset split given for `hi` dataset.
+
+```python
+DatasetDict({
+    train: Dataset({
+        features: ['utterance', 'logical form', 'intent'],
+        num_rows: 392702
+    })
+    test: Dataset({
+        features: ['utterance', 'logical form', 'intent'],
+        num_rows: 5010
+    })
+    validation: Dataset({
+        features: ['utterance', 'logical form', 'intent'],
+        num_rows: 2490
+    })
+})
+
+``` -->
+
+Language      | ISO 639-1 Code |Train | Dev | Test |
+--------------|----------------|-------|-----|------|
+Assamese | as | 392,702 | 5,010 | 2,490 |
+Bengali | bn | 392,702 | 5,010 | 2,490 |
+Gujarati | gu |  392,702 | 5,010 | 2,490 |
+Hindi | hi | 392,702 | 5,010 | 2,490 |
+Kannada | kn |  392,702 | 5,010 | 2,490 |
+Malayalam | ml |392,702  | 5,010 | 2,490 |
+Marathi | mr |392,702 | 5,010 | 2,490 |
+Oriya | or | 392,702 | 5,010 | 2,490 |
+Punjabi | pa | 392,702 | 5,010 | 2,490 |
+Tamil | ta | 392,702 | 5,010 | 2,490 |
+Telugu | te | 392,702 | 5,010 | 2,490 |
+
+<!-- The dataset split remains same across all languages. -->
+
+## Dataset usage
+
+Code snippet for using the dataset using datasets library.
+
+```python
+from datasets import load_dataset
+
+dataset = load_dataset("Divyanshu/indicxnli")
+```
+
+## Dataset Creation
+
+Machine translation of XNLI english dataset to 11 listed Indic Languages.
+
+### Curation Rationale
+
+[More information needed]
+
+### Source Data
+
+[XNLI dataset](https://cims.nyu.edu/~sbowman/xnli/)
+
+#### Initial Data Collection and Normalization
+
+[Detailed in the paper](https://arxiv.org/abs/2304.13005)
+
+#### Who are the source language producers?
+
+[Detailed in the paper](https://arxiv.org/abs/2304.13005)
+
+#### Human Verification Process
+
+[Detailed in the paper](https://arxiv.org/abs/2304.13005)
+
+## Considerations for Using the Data
+
+### Social Impact of Dataset
+
+[Detailed in the paper](https://arxiv.org/abs/2304.13005)
+
+### Discussion of Biases
+
+[Detailed in the paper](https://arxiv.org/abs/2304.13005)
+
+### Other Known Limitations
+
+[Detailed in the paper](https://arxiv.org/abs/2304.13005)
+
+### Dataset Curators
+
+Divyanshu Aggarwal, Vivek Gupta, Anoop Kunchukuttan
+
+### Licensing Information
+
+Contents of this repository are restricted to only non-commercial research purposes under the [Creative Commons Attribution-NonCommercial 4.0 International License (CC BY-NC 4.0)](https://creativecommons.org/licenses/by-nc/4.0/). Copyright of the dataset contents belongs to the original copyright holders.
+
+### Citation Information
+
+If you use any of the datasets, models or code modules, please cite the following paper:
+
+```
+@misc{https://doi.org/10.48550/arxiv.2204.08776,
+  doi = {10.48550/ARXIV.2204.08776},
+  
+  url = {https://arxiv.org/abs/2304.13005},
+  
+  author = {Aggarwal, Divyanshu and Gupta, Vivek and Kunchukuttan, Anoop},
+  
+  keywords = {Computation and Language (cs.CL), Artificial Intelligence (cs.AI), FOS: Computer and information sciences, FOS: Computer and information sciences},
+  
+  title = {IE-SemParse: Evaluating Multilingual Inference for Indian Languages}, 
+  
+  publisher = {arXiv},
+  
+  year = {2022},
+  
+  copyright = {Creative Commons Attribution 4.0 International}
+}
+```
+
+<!-- ### Contributions -->

.history/README_20230707233805.md

@@ -0,0 +1,214 @@
+---
+annotations_creators:
+- machine-generated
+language_creators:
+- machine-generated
+language:
+- as
+- bn
+- gu
+- hi
+- kn
+- ml
+- mr
+- or
+- pa
+- ta
+- te
+license:
+- cc0-1.0
+multilinguality:
+- multilingual
+pretty_name: IE-SemParse
+size_categories:
+- 1M<n<10M
+source_datasets:
+- original
+task_categories:
+- text2text
+task_ids:
+- Semantic-Parsing
+---
+
+# Dataset Card for "IE-SemParse"
+
+## Table of Contents
+
+- [Dataset Card for "IE-SemParse"](#dataset-card-for-ie-semparse)
+  - [Table of Contents](#table-of-contents)
+  - [Dataset Description](#dataset-description)
+    - [Dataset Summary](#dataset-summary)
+    - [Supported Tasks and Leaderboards](#supported-tasks-and-leaderboards)
+    - [Languages](#languages)
+    - [Data Splits](#data-splits)
+  - [Dataset usage](#dataset-usage)
+  - [Dataset Creation](#dataset-creation)
+    - [Curation Rationale](#curation-rationale)
+    - [Source Data](#source-data)
+      - [Initial Data Collection and Normalization](#initial-data-collection-and-normalization)
+      - [Who are the source language producers?](#who-are-the-source-language-producers)
+      - [Human Verification Process](#human-verification-process)
+  - [Considerations for Using the Data](#considerations-for-using-the-data)
+    - [Social Impact of Dataset](#social-impact-of-dataset)
+    - [Discussion of Biases](#discussion-of-biases)
+    - [Other Known Limitations](#other-known-limitations)
+    - [Dataset Curators](#dataset-curators)
+    - [Licensing Information](#licensing-information)
+    - [Citation Information](#citation-information)
+
+## Dataset Description
+
+- **Homepage:** <https://github.com/divyanshuaggarwal/IE-SemParse>
+- **Paper:** [Evaluating Inter-Bilingual Semantic Parsing for Indian Languages](https://arxiv.org/abs/2304.13005)
+- **Point of Contact:** [Divyanshu Aggarwal](mailto:[email protected])
+
+### Dataset Summary
+
+IE-SemParse is an InterBilingual Semantic Parsing Dataset for eleven major Indic languages that includes
+Assamese (‘as’), Gujarat (‘gu’), Kannada (‘kn’),
+Malayalam (‘ml’), Marathi (‘mr’), Odia (‘or’),
+Punjabi (‘pa’), Tamil (‘ta’), Telugu (‘te’), Hindi
+(‘hi’), and Bengali (‘bn’).
+
+### Supported Tasks and Leaderboards
+
+**Tasks:** Natural Language Inference
+
+**Leaderboards:** Currently there is no Leaderboard for this dataset.
+
+### Languages
+
+- `Assamese (as)`
+- `Bengali (bn)`
+- `Gujarati (gu)`
+- `Kannada (kn)`
+- `Hindi (hi)`
+- `Malayalam (ml)`
+- `Marathi (mr)`
+- `Oriya (or)`
+- `Punjabi (pa)`
+- `Tamil (ta)`
+- `Telugu (te)`
+
+...
+
+
+### Data Splits
+
+<!-- Below is the dataset split given for `hi` dataset.
+
+```python
+DatasetDict({
+    train: Dataset({
+        features: ['utterance', 'logical form', 'intent'],
+        num_rows: 
+    })
+    test: Dataset({
+        features: ['utterance', 'logical form', 'intent'],
+        num_rows: 5010
+    })
+    validation: Dataset({
+        features: ['utterance', 'logical form', 'intent'],
+        num_rows: 2490
+    })
+})
+
+``` -->
+
+Language      | ISO 639-1 Code |Train | Dev | Test |
+--------------|----------------|-------|-----|------|
+Assamese | as | 392,702 | 5,010 | 2,490 |
+Bengali | bn | 392,702 | 5,010 | 2,490 |
+Gujarati | gu |  392,702 | 5,010 | 2,490 |
+Hindi | hi | 392,702 | 5,010 | 2,490 |
+Kannada | kn |  392,702 | 5,010 | 2,490 |
+Malayalam | ml |392,702  | 5,010 | 2,490 |
+Marathi | mr |392,702 | 5,010 | 2,490 |
+Oriya | or | 392,702 | 5,010 | 2,490 |
+Punjabi | pa | 392,702 | 5,010 | 2,490 |
+Tamil | ta | 392,702 | 5,010 | 2,490 |
+Telugu | te | 392,702 | 5,010 | 2,490 |
+
+<!-- The dataset split remains same across all languages. -->
+
+## Dataset usage
+
+Code snippet for using the dataset using datasets library.
+
+```python
+from datasets import load_dataset
+
+dataset = load_dataset("Divyanshu/indicxnli")
+```
+
+## Dataset Creation
+
+Machine translation of XNLI english dataset to 11 listed Indic Languages.
+
+### Curation Rationale
+
+[More information needed]
+
+### Source Data
+
+[XNLI dataset](https://cims.nyu.edu/~sbowman/xnli/)
+
+#### Initial Data Collection and Normalization
+
+[Detailed in the paper](https://arxiv.org/abs/2304.13005)
+
+#### Who are the source language producers?
+
+[Detailed in the paper](https://arxiv.org/abs/2304.13005)
+
+#### Human Verification Process
+
+[Detailed in the paper](https://arxiv.org/abs/2304.13005)
+
+## Considerations for Using the Data
+
+### Social Impact of Dataset
+
+[Detailed in the paper](https://arxiv.org/abs/2304.13005)
+
+### Discussion of Biases
+
+[Detailed in the paper](https://arxiv.org/abs/2304.13005)
+
+### Other Known Limitations
+
+[Detailed in the paper](https://arxiv.org/abs/2304.13005)
+
+### Dataset Curators
+
+Divyanshu Aggarwal, Vivek Gupta, Anoop Kunchukuttan
+
+### Licensing Information
+
+Contents of this repository are restricted to only non-commercial research purposes under the [Creative Commons Attribution-NonCommercial 4.0 International License (CC BY-NC 4.0)](https://creativecommons.org/licenses/by-nc/4.0/). Copyright of the dataset contents belongs to the original copyright holders.
+
+### Citation Information
+
+If you use any of the datasets, models or code modules, please cite the following paper:
+
+```
+@misc{https://doi.org/10.48550/arxiv.2204.08776,
+  doi = {10.48550/ARXIV.2204.08776},
+  
+  url = {https://arxiv.org/abs/2304.13005},
+  
+  author = {Aggarwal, Divyanshu and Gupta, Vivek and Kunchukuttan, Anoop},
+  
+  keywords = {Computation and Language (cs.CL), Artificial Intelligence (cs.AI), FOS: Computer and information sciences, FOS: Computer and information sciences},
+  
+  title = {IE-SemParse: Evaluating Multilingual Inference for Indian Languages}, 
+  
+  publisher = {arXiv},
+  
+  year = {2022},
+  
+  copyright = {Creative Commons Attribution 4.0 International}
+}
+```
+
+<!-- ### Contributions -->

.history/README_20230707233808.md

@@ -0,0 +1,214 @@
+---
+annotations_creators:
+- machine-generated
+language_creators:
+- machine-generated
+language:
+- as
+- bn
+- gu
+- hi
+- kn
+- ml
+- mr
+- or
+- pa
+- ta
+- te
+license:
+- cc0-1.0
+multilinguality:
+- multilingual
+pretty_name: IE-SemParse
+size_categories:
+- 1M<n<10M
+source_datasets:
+- original
+task_categories:
+- text2text
+task_ids:
+- Semantic-Parsing
+---
+
+# Dataset Card for "IE-SemParse"
+
+## Table of Contents
+
+- [Dataset Card for "IE-SemParse"](#dataset-card-for-ie-semparse)
+  - [Table of Contents](#table-of-contents)
+  - [Dataset Description](#dataset-description)
+    - [Dataset Summary](#dataset-summary)
+    - [Supported Tasks and Leaderboards](#supported-tasks-and-leaderboards)
+    - [Languages](#languages)
+    - [Data Splits](#data-splits)
+  - [Dataset usage](#dataset-usage)
+  - [Dataset Creation](#dataset-creation)
+    - [Curation Rationale](#curation-rationale)
+    - [Source Data](#source-data)
+      - [Initial Data Collection and Normalization](#initial-data-collection-and-normalization)
+      - [Who are the source language producers?](#who-are-the-source-language-producers)
+      - [Human Verification Process](#human-verification-process)
+  - [Considerations for Using the Data](#considerations-for-using-the-data)
+    - [Social Impact of Dataset](#social-impact-of-dataset)
+    - [Discussion of Biases](#discussion-of-biases)
+    - [Other Known Limitations](#other-known-limitations)
+    - [Dataset Curators](#dataset-curators)
+    - [Licensing Information](#licensing-information)
+    - [Citation Information](#citation-information)
+
+## Dataset Description
+
+- **Homepage:** <https://github.com/divyanshuaggarwal/IE-SemParse>
+- **Paper:** [Evaluating Inter-Bilingual Semantic Parsing for Indian Languages](https://arxiv.org/abs/2304.13005)
+- **Point of Contact:** [Divyanshu Aggarwal](mailto:[email protected])
+
+### Dataset Summary
+
+IE-SemParse is an InterBilingual Semantic Parsing Dataset for eleven major Indic languages that includes
+Assamese (‘as’), Gujarat (‘gu’), Kannada (‘kn’),
+Malayalam (‘ml’), Marathi (‘mr’), Odia (‘or’),
+Punjabi (‘pa’), Tamil (‘ta’), Telugu (‘te’), Hindi
+(‘hi’), and Bengali (‘bn’).
+
+### Supported Tasks and Leaderboards
+
+**Tasks:** Natural Language Inference
+
+**Leaderboards:** Currently there is no Leaderboard for this dataset.
+
+### Languages
+
+- `Assamese (as)`
+- `Bengali (bn)`
+- `Gujarati (gu)`
+- `Kannada (kn)`
+- `Hindi (hi)`
+- `Malayalam (ml)`
+- `Marathi (mr)`
+- `Oriya (or)`
+- `Punjabi (pa)`
+- `Tamil (ta)`
+- `Telugu (te)`
+
+...
+
+
+### Data Splits
+
+<!-- Below is the dataset split given for `hi` dataset.
+
+```python
+DatasetDict({
+    train: Dataset({
+        features: ['utterance', 'logical form', 'intent'],
+        num_rows: 36000
+    })
+    test: Dataset({
+        features: ['utterance', 'logical form', 'intent'],
+        num_rows: 5010
+    })
+    validation: Dataset({
+        features: ['utterance', 'logical form', 'intent'],
+        num_rows: 2490
+    })
+})
+
+``` -->
+
+Language      | ISO 639-1 Code |Train | Dev | Test |
+--------------|----------------|-------|-----|------|
+Assamese | as | 392,702 | 5,010 | 2,490 |
+Bengali | bn | 392,702 | 5,010 | 2,490 |
+Gujarati | gu |  392,702 | 5,010 | 2,490 |
+Hindi | hi | 392,702 | 5,010 | 2,490 |
+Kannada | kn |  392,702 | 5,010 | 2,490 |
+Malayalam | ml |392,702  | 5,010 | 2,490 |
+Marathi | mr |392,702 | 5,010 | 2,490 |
+Oriya | or | 392,702 | 5,010 | 2,490 |
+Punjabi | pa | 392,702 | 5,010 | 2,490 |
+Tamil | ta | 392,702 | 5,010 | 2,490 |
+Telugu | te | 392,702 | 5,010 | 2,490 |
+
+<!-- The dataset split remains same across all languages. -->
+
+## Dataset usage
+
+Code snippet for using the dataset using datasets library.
+
+```python
+from datasets import load_dataset
+
+dataset = load_dataset("Divyanshu/indicxnli")
+```
+
+## Dataset Creation
+
+Machine translation of XNLI english dataset to 11 listed Indic Languages.
+
+### Curation Rationale
+
+[More information needed]
+
+### Source Data
+
+[XNLI dataset](https://cims.nyu.edu/~sbowman/xnli/)
+
+#### Initial Data Collection and Normalization
+
+[Detailed in the paper](https://arxiv.org/abs/2304.13005)
+
+#### Who are the source language producers?
+
+[Detailed in the paper](https://arxiv.org/abs/2304.13005)
+
+#### Human Verification Process
+
+[Detailed in the paper](https://arxiv.org/abs/2304.13005)
+
+## Considerations for Using the Data
+
+### Social Impact of Dataset
+
+[Detailed in the paper](https://arxiv.org/abs/2304.13005)
+
+### Discussion of Biases
+
+[Detailed in the paper](https://arxiv.org/abs/2304.13005)
+
+### Other Known Limitations
+
+[Detailed in the paper](https://arxiv.org/abs/2304.13005)
+
+### Dataset Curators
+
+Divyanshu Aggarwal, Vivek Gupta, Anoop Kunchukuttan
+
+### Licensing Information
+
+Contents of this repository are restricted to only non-commercial research purposes under the [Creative Commons Attribution-NonCommercial 4.0 International License (CC BY-NC 4.0)](https://creativecommons.org/licenses/by-nc/4.0/). Copyright of the dataset contents belongs to the original copyright holders.
+
+### Citation Information
+
+If you use any of the datasets, models or code modules, please cite the following paper:
+
+```
+@misc{https://doi.org/10.48550/arxiv.2204.08776,
+  doi = {10.48550/ARXIV.2204.08776},
+  
+  url = {https://arxiv.org/abs/2304.13005},
+  
+  author = {Aggarwal, Divyanshu and Gupta, Vivek and Kunchukuttan, Anoop},
+  
+  keywords = {Computation and Language (cs.CL), Artificial Intelligence (cs.AI), FOS: Computer and information sciences, FOS: Computer and information sciences},
+  
+  title = {IE-SemParse: Evaluating Multilingual Inference for Indian Languages}, 
+  
+  publisher = {arXiv},
+  
+  year = {2022},
+  
+  copyright = {Creative Commons Attribution 4.0 International}
+}
+```
+
+<!-- ### Contributions -->

.history/README_20230707233812.md

@@ -0,0 +1,214 @@
+---
+annotations_creators:
+- machine-generated
+language_creators:
+- machine-generated
+language:
+- as
+- bn
+- gu
+- hi
+- kn
+- ml
+- mr
+- or
+- pa
+- ta
+- te
+license:
+- cc0-1.0
+multilinguality:
+- multilingual
+pretty_name: IE-SemParse
+size_categories:
+- 1M<n<10M
+source_datasets:
+- original
+task_categories:
+- text2text
+task_ids:
+- Semantic-Parsing
+---
+
+# Dataset Card for "IE-SemParse"
+
+## Table of Contents
+
+- [Dataset Card for "IE-SemParse"](#dataset-card-for-ie-semparse)
+  - [Table of Contents](#table-of-contents)
+  - [Dataset Description](#dataset-description)
+    - [Dataset Summary](#dataset-summary)
+    - [Supported Tasks and Leaderboards](#supported-tasks-and-leaderboards)
+    - [Languages](#languages)
+    - [Data Splits](#data-splits)
+  - [Dataset usage](#dataset-usage)
+  - [Dataset Creation](#dataset-creation)
+    - [Curation Rationale](#curation-rationale)
+    - [Source Data](#source-data)
+      - [Initial Data Collection and Normalization](#initial-data-collection-and-normalization)
+      - [Who are the source language producers?](#who-are-the-source-language-producers)
+      - [Human Verification Process](#human-verification-process)
+  - [Considerations for Using the Data](#considerations-for-using-the-data)
+    - [Social Impact of Dataset](#social-impact-of-dataset)
+    - [Discussion of Biases](#discussion-of-biases)
+    - [Other Known Limitations](#other-known-limitations)
+    - [Dataset Curators](#dataset-curators)
+    - [Licensing Information](#licensing-information)
+    - [Citation Information](#citation-information)
+
+## Dataset Description
+
+- **Homepage:** <https://github.com/divyanshuaggarwal/IE-SemParse>
+- **Paper:** [Evaluating Inter-Bilingual Semantic Parsing for Indian Languages](https://arxiv.org/abs/2304.13005)
+- **Point of Contact:** [Divyanshu Aggarwal](mailto:[email protected])
+
+### Dataset Summary
+
+IE-SemParse is an InterBilingual Semantic Parsing Dataset for eleven major Indic languages that includes
+Assamese (‘as’), Gujarat (‘gu’), Kannada (‘kn’),
+Malayalam (‘ml’), Marathi (‘mr’), Odia (‘or’),
+Punjabi (‘pa’), Tamil (‘ta’), Telugu (‘te’), Hindi
+(‘hi’), and Bengali (‘bn’).
+
+### Supported Tasks and Leaderboards
+
+**Tasks:** Natural Language Inference
+
+**Leaderboards:** Currently there is no Leaderboard for this dataset.
+
+### Languages
+
+- `Assamese (as)`
+- `Bengali (bn)`
+- `Gujarati (gu)`
+- `Kannada (kn)`
+- `Hindi (hi)`
+- `Malayalam (ml)`
+- `Marathi (mr)`
+- `Oriya (or)`
+- `Punjabi (pa)`
+- `Tamil (ta)`
+- `Telugu (te)`
+
+...
+
+
+### Data Splits
+
+<!-- Below is the dataset split given for `hi` dataset.
+
+```python
+DatasetDict({
+    train: Dataset({
+        features: ['utterance', 'logical form', 'intent'],
+        num_rows: 36000
+    })
+    test: Dataset({
+        features: ['utterance', 'logical form', 'intent'],
+        num_rows: 3000
+    })
+    validation: Dataset({
+        features: ['utterance', 'logical form', 'intent'],
+        num_rows: 2490
+    })
+})
+
+``` -->
+
+Language      | ISO 639-1 Code |Train | Dev | Test |
+--------------|----------------|-------|-----|------|
+Assamese | as | 392,702 | 5,010 | 2,490 |
+Bengali | bn | 392,702 | 5,010 | 2,490 |
+Gujarati | gu |  392,702 | 5,010 | 2,490 |
+Hindi | hi | 392,702 | 5,010 | 2,490 |
+Kannada | kn |  392,702 | 5,010 | 2,490 |
+Malayalam | ml |392,702  | 5,010 | 2,490 |
+Marathi | mr |392,702 | 5,010 | 2,490 |
+Oriya | or | 392,702 | 5,010 | 2,490 |
+Punjabi | pa | 392,702 | 5,010 | 2,490 |
+Tamil | ta | 392,702 | 5,010 | 2,490 |
+Telugu | te | 392,702 | 5,010 | 2,490 |
+
+<!-- The dataset split remains same across all languages. -->
+
+## Dataset usage
+
+Code snippet for using the dataset using datasets library.
+
+```python
+from datasets import load_dataset
+
+dataset = load_dataset("Divyanshu/indicxnli")
+```
+
+## Dataset Creation
+
+Machine translation of XNLI english dataset to 11 listed Indic Languages.
+
+### Curation Rationale
+
+[More information needed]
+
+### Source Data
+
+[XNLI dataset](https://cims.nyu.edu/~sbowman/xnli/)
+
+#### Initial Data Collection and Normalization
+
+[Detailed in the paper](https://arxiv.org/abs/2304.13005)
+
+#### Who are the source language producers?
+
+[Detailed in the paper](https://arxiv.org/abs/2304.13005)
+
+#### Human Verification Process
+
+[Detailed in the paper](https://arxiv.org/abs/2304.13005)
+
+## Considerations for Using the Data
+
+### Social Impact of Dataset
+
+[Detailed in the paper](https://arxiv.org/abs/2304.13005)
+
+### Discussion of Biases
+
+[Detailed in the paper](https://arxiv.org/abs/2304.13005)
+
+### Other Known Limitations
+
+[Detailed in the paper](https://arxiv.org/abs/2304.13005)
+
+### Dataset Curators
+
+Divyanshu Aggarwal, Vivek Gupta, Anoop Kunchukuttan
+
+### Licensing Information
+
+Contents of this repository are restricted to only non-commercial research purposes under the [Creative Commons Attribution-NonCommercial 4.0 International License (CC BY-NC 4.0)](https://creativecommons.org/licenses/by-nc/4.0/). Copyright of the dataset contents belongs to the original copyright holders.
+
+### Citation Information
+
+If you use any of the datasets, models or code modules, please cite the following paper:
+
+```
+@misc{https://doi.org/10.48550/arxiv.2204.08776,
+  doi = {10.48550/ARXIV.2204.08776},
+  
+  url = {https://arxiv.org/abs/2304.13005},
+  
+  author = {Aggarwal, Divyanshu and Gupta, Vivek and Kunchukuttan, Anoop},
+  
+  keywords = {Computation and Language (cs.CL), Artificial Intelligence (cs.AI), FOS: Computer and information sciences, FOS: Computer and information sciences},
+  
+  title = {IE-SemParse: Evaluating Multilingual Inference for Indian Languages}, 
+  
+  publisher = {arXiv},
+  
+  year = {2022},
+  
+  copyright = {Creative Commons Attribution 4.0 International}
+}
+```
+
+<!-- ### Contributions -->

.history/README_20230707233815.md

@@ -0,0 +1,214 @@
+---
+annotations_creators:
+- machine-generated
+language_creators:
+- machine-generated
+language:
+- as
+- bn
+- gu
+- hi
+- kn
+- ml
+- mr
+- or
+- pa
+- ta
+- te
+license:
+- cc0-1.0
+multilinguality:
+- multilingual
+pretty_name: IE-SemParse
+size_categories:
+- 1M<n<10M
+source_datasets:
+- original
+task_categories:
+- text2text
+task_ids:
+- Semantic-Parsing
+---
+
+# Dataset Card for "IE-SemParse"
+
+## Table of Contents
+
+- [Dataset Card for "IE-SemParse"](#dataset-card-for-ie-semparse)
+  - [Table of Contents](#table-of-contents)
+  - [Dataset Description](#dataset-description)
+    - [Dataset Summary](#dataset-summary)
+    - [Supported Tasks and Leaderboards](#supported-tasks-and-leaderboards)
+    - [Languages](#languages)
+    - [Data Splits](#data-splits)
+  - [Dataset usage](#dataset-usage)
+  - [Dataset Creation](#dataset-creation)
+    - [Curation Rationale](#curation-rationale)
+    - [Source Data](#source-data)
+      - [Initial Data Collection and Normalization](#initial-data-collection-and-normalization)
+      - [Who are the source language producers?](#who-are-the-source-language-producers)
+      - [Human Verification Process](#human-verification-process)
+  - [Considerations for Using the Data](#considerations-for-using-the-data)
+    - [Social Impact of Dataset](#social-impact-of-dataset)
+    - [Discussion of Biases](#discussion-of-biases)
+    - [Other Known Limitations](#other-known-limitations)
+    - [Dataset Curators](#dataset-curators)
+    - [Licensing Information](#licensing-information)
+    - [Citation Information](#citation-information)
+
+## Dataset Description
+
+- **Homepage:** <https://github.com/divyanshuaggarwal/IE-SemParse>
+- **Paper:** [Evaluating Inter-Bilingual Semantic Parsing for Indian Languages](https://arxiv.org/abs/2304.13005)
+- **Point of Contact:** [Divyanshu Aggarwal](mailto:[email protected])
+
+### Dataset Summary
+
+IE-SemParse is an InterBilingual Semantic Parsing Dataset for eleven major Indic languages that includes
+Assamese (‘as’), Gujarat (‘gu’), Kannada (‘kn’),
+Malayalam (‘ml’), Marathi (‘mr’), Odia (‘or’),
+Punjabi (‘pa’), Tamil (‘ta’), Telugu (‘te’), Hindi
+(‘hi’), and Bengali (‘bn’).
+
+### Supported Tasks and Leaderboards
+
+**Tasks:** Natural Language Inference
+
+**Leaderboards:** Currently there is no Leaderboard for this dataset.
+
+### Languages
+
+- `Assamese (as)`
+- `Bengali (bn)`
+- `Gujarati (gu)`
+- `Kannada (kn)`
+- `Hindi (hi)`
+- `Malayalam (ml)`
+- `Marathi (mr)`
+- `Oriya (or)`
+- `Punjabi (pa)`
+- `Tamil (ta)`
+- `Telugu (te)`
+
+...
+
+
+### Data Splits
+
+<!-- Below is the dataset split given for `hi` dataset.
+
+```python
+DatasetDict({
+    train: Dataset({
+        features: ['utterance', 'logical form', 'intent'],
+        num_rows: 36000
+    })
+    test: Dataset({
+        features: ['utterance', 'logical form', 'intent'],
+        num_rows: 3000
+    })
+    validation: Dataset({
+        features: ['utterance', 'logical form', 'intent'],
+        num_rows: 1500
+    })
+})
+
+``` -->
+
+Language      | ISO 639-1 Code |Train | Dev | Test |
+--------------|----------------|-------|-----|------|
+Assamese | as | 392,702 | 5,010 | 2,490 |
+Bengali | bn | 392,702 | 5,010 | 2,490 |
+Gujarati | gu |  392,702 | 5,010 | 2,490 |
+Hindi | hi | 392,702 | 5,010 | 2,490 |
+Kannada | kn |  392,702 | 5,010 | 2,490 |
+Malayalam | ml |392,702  | 5,010 | 2,490 |
+Marathi | mr |392,702 | 5,010 | 2,490 |
+Oriya | or | 392,702 | 5,010 | 2,490 |
+Punjabi | pa | 392,702 | 5,010 | 2,490 |
+Tamil | ta | 392,702 | 5,010 | 2,490 |
+Telugu | te | 392,702 | 5,010 | 2,490 |
+
+<!-- The dataset split remains same across all languages. -->
+
+## Dataset usage
+
+Code snippet for using the dataset using datasets library.
+
+```python
+from datasets import load_dataset
+
+dataset = load_dataset("Divyanshu/indicxnli")
+```
+
+## Dataset Creation
+
+Machine translation of XNLI english dataset to 11 listed Indic Languages.
+
+### Curation Rationale
+
+[More information needed]
+
+### Source Data
+
+[XNLI dataset](https://cims.nyu.edu/~sbowman/xnli/)
+
+#### Initial Data Collection and Normalization
+
+[Detailed in the paper](https://arxiv.org/abs/2304.13005)
+
+#### Who are the source language producers?
+
+[Detailed in the paper](https://arxiv.org/abs/2304.13005)
+
+#### Human Verification Process
+
+[Detailed in the paper](https://arxiv.org/abs/2304.13005)
+
+## Considerations for Using the Data
+
+### Social Impact of Dataset
+
+[Detailed in the paper](https://arxiv.org/abs/2304.13005)
+
+### Discussion of Biases
+
+[Detailed in the paper](https://arxiv.org/abs/2304.13005)
+
+### Other Known Limitations
+
+[Detailed in the paper](https://arxiv.org/abs/2304.13005)
+
+### Dataset Curators
+
+Divyanshu Aggarwal, Vivek Gupta, Anoop Kunchukuttan
+
+### Licensing Information
+
+Contents of this repository are restricted to only non-commercial research purposes under the [Creative Commons Attribution-NonCommercial 4.0 International License (CC BY-NC 4.0)](https://creativecommons.org/licenses/by-nc/4.0/). Copyright of the dataset contents belongs to the original copyright holders.
+
+### Citation Information
+
+If you use any of the datasets, models or code modules, please cite the following paper:
+
+```
+@misc{https://doi.org/10.48550/arxiv.2204.08776,
+  doi = {10.48550/ARXIV.2204.08776},
+  
+  url = {https://arxiv.org/abs/2304.13005},
+  
+  author = {Aggarwal, Divyanshu and Gupta, Vivek and Kunchukuttan, Anoop},
+  
+  keywords = {Computation and Language (cs.CL), Artificial Intelligence (cs.AI), FOS: Computer and information sciences, FOS: Computer and information sciences},
+  
+  title = {IE-SemParse: Evaluating Multilingual Inference for Indian Languages}, 
+  
+  publisher = {arXiv},
+  
+  year = {2022},
+  
+  copyright = {Creative Commons Attribution 4.0 International}
+}
+```
+
+<!-- ### Contributions -->

IE-SemParse.py

@@ -55,7 +55,7 @@ _DATASETS = (
 _URL = "https://huggingface.co/datasets/Divyanshu/IE-SemParse/resolve/main/"
 
 
-class IESemParseConfig(datasets.BuilderConfig):
+class IE_SemParseConfig(datasets.BuilderConfig):
     """BuilderConfig for IE-SemParse."""
 
     def __init__(self, dataset: str, language: str, **kwargs):
@@ -65,7 +65,7 @@ class IESemParseConfig(datasets.BuilderConfig):
         language: One of hi, bn, mr, as, ta, te, or, ml, pa, gu, kn
           **kwargs: keyword arguments forwarded to super.
         """
-        super(IESemParseConfig, self).__init__(**kwargs)
+        super(IE_SemParseConfig, self).__init__(**kwargs)
 
         self.dataset = dataset
         self.language = language
@@ -76,13 +76,13 @@ class IESemParseConfig(datasets.BuilderConfig):
             _URL, "unfiltered_data", dataset, f"{language}.json")]
 
 
-class IESemParse(datasets.GeneratorBasedBuilder):
+class IE_SemParse(datasets.GeneratorBasedBuilder):
     """IE-SemParse: Inter-Bilingual Semantic Parsing Dataset for Indic Languages. Version 1.0."""
 
     VERSION = datasets.Version("1.0.0", "")
-    BUILDER_CONFIG_CLASS = IESemParseConfig
+    BUILDER_CONFIG_CLASS = IE_SemParseConfig
     BUILDER_CONFIGS = [
-        IESemParseConfig(
+        IE_SemParseConfig(
             name=f"{dataset}_{language}",
             language=language,
             dataset=dataset,

README.md

@@ -1,3 +1,214 @@
 ---
-license: mit
+annotations_creators:
+- machine-generated
+language_creators:
+- machine-generated
+language:
+- as
+- bn
+- gu
+- hi
+- kn
+- ml
+- mr
+- or
+- pa
+- ta
+- te
+license:
+- cc0-1.0
+multilinguality:
+- multilingual
+pretty_name: IE-SemParse
+size_categories:
+- 1M<n<10M
+source_datasets:
+- original
+task_categories:
+- text2text
+task_ids:
+- Semantic-Parsing
 ---
+
+# Dataset Card for "IE-SemParse"
+
+## Table of Contents
+
+- [Dataset Card for "IE-SemParse"](#dataset-card-for-ie-semparse)
+  - [Table of Contents](#table-of-contents)
+  - [Dataset Description](#dataset-description)
+    - [Dataset Summary](#dataset-summary)
+    - [Supported Tasks and Leaderboards](#supported-tasks-and-leaderboards)
+    - [Languages](#languages)
+    - [Data Splits](#data-splits)
+  - [Dataset usage](#dataset-usage)
+  - [Dataset Creation](#dataset-creation)
+    - [Curation Rationale](#curation-rationale)
+    - [Source Data](#source-data)
+      - [Initial Data Collection and Normalization](#initial-data-collection-and-normalization)
+      - [Who are the source language producers?](#who-are-the-source-language-producers)
+      - [Human Verification Process](#human-verification-process)
+  - [Considerations for Using the Data](#considerations-for-using-the-data)
+    - [Social Impact of Dataset](#social-impact-of-dataset)
+    - [Discussion of Biases](#discussion-of-biases)
+    - [Other Known Limitations](#other-known-limitations)
+    - [Dataset Curators](#dataset-curators)
+    - [Licensing Information](#licensing-information)
+    - [Citation Information](#citation-information)
+
+## Dataset Description
+
+- **Homepage:** <https://github.com/divyanshuaggarwal/IE-SemParse>
+- **Paper:** [Evaluating Inter-Bilingual Semantic Parsing for Indian Languages](https://arxiv.org/abs/2304.13005)
+- **Point of Contact:** [Divyanshu Aggarwal](mailto:[email protected])
+
+### Dataset Summary
+
+IE-SemParse is an InterBilingual Semantic Parsing Dataset for eleven major Indic languages that includes
+Assamese (‘as’), Gujarat (‘gu’), Kannada (‘kn’),
+Malayalam (‘ml’), Marathi (‘mr’), Odia (‘or’),
+Punjabi (‘pa’), Tamil (‘ta’), Telugu (‘te’), Hindi
+(‘hi’), and Bengali (‘bn’).
+
+### Supported Tasks and Leaderboards
+
+**Tasks:** Natural Language Inference
+
+**Leaderboards:** Currently there is no Leaderboard for this dataset.
+
+### Languages
+
+- `Assamese (as)`
+- `Bengali (bn)`
+- `Gujarati (gu)`
+- `Kannada (kn)`
+- `Hindi (hi)`
+- `Malayalam (ml)`
+- `Marathi (mr)`
+- `Oriya (or)`
+- `Punjabi (pa)`
+- `Tamil (ta)`
+- `Telugu (te)`
+
+...
+
+
+### Data Splits
+
+<!-- Below is the dataset split given for `hi` dataset.
+
+```python
+DatasetDict({
+    train: Dataset({
+        features: ['utterance', 'logical form', 'intent'],
+        num_rows: 36000
+    })
+    test: Dataset({
+        features: ['utterance', 'logical form', 'intent'],
+        num_rows: 3000
+    })
+    validation: Dataset({
+        features: ['utterance', 'logical form', 'intent'],
+        num_rows: 1500
+    })
+})
+
+``` -->
+
+Language      | ISO 639-1 Code |Train | Dev | Test |
+--------------|----------------|-------|-----|------|
+Assamese | as | 392,702 | 5,010 | 2,490 |
+Bengali | bn | 392,702 | 5,010 | 2,490 |
+Gujarati | gu |  392,702 | 5,010 | 2,490 |
+Hindi | hi | 392,702 | 5,010 | 2,490 |
+Kannada | kn |  392,702 | 5,010 | 2,490 |
+Malayalam | ml |392,702  | 5,010 | 2,490 |
+Marathi | mr |392,702 | 5,010 | 2,490 |
+Oriya | or | 392,702 | 5,010 | 2,490 |
+Punjabi | pa | 392,702 | 5,010 | 2,490 |
+Tamil | ta | 392,702 | 5,010 | 2,490 |
+Telugu | te | 392,702 | 5,010 | 2,490 |
+
+<!-- The dataset split remains same across all languages. -->
+
+## Dataset usage
+
+Code snippet for using the dataset using datasets library.
+
+```python
+from datasets import load_dataset
+
+dataset = load_dataset("Divyanshu/indicxnli")
+```
+
+## Dataset Creation
+
+Machine translation of XNLI english dataset to 11 listed Indic Languages.
+
+### Curation Rationale
+
+[More information needed]
+
+### Source Data
+
+[XNLI dataset](https://cims.nyu.edu/~sbowman/xnli/)
+
+#### Initial Data Collection and Normalization
+
+[Detailed in the paper](https://arxiv.org/abs/2304.13005)
+
+#### Who are the source language producers?
+
+[Detailed in the paper](https://arxiv.org/abs/2304.13005)
+
+#### Human Verification Process
+
+[Detailed in the paper](https://arxiv.org/abs/2304.13005)
+
+## Considerations for Using the Data
+
+### Social Impact of Dataset
+
+[Detailed in the paper](https://arxiv.org/abs/2304.13005)
+
+### Discussion of Biases
+
+[Detailed in the paper](https://arxiv.org/abs/2304.13005)
+
+### Other Known Limitations
+
+[Detailed in the paper](https://arxiv.org/abs/2304.13005)
+
+### Dataset Curators
+
+Divyanshu Aggarwal, Vivek Gupta, Anoop Kunchukuttan
+
+### Licensing Information
+
+Contents of this repository are restricted to only non-commercial research purposes under the [Creative Commons Attribution-NonCommercial 4.0 International License (CC BY-NC 4.0)](https://creativecommons.org/licenses/by-nc/4.0/). Copyright of the dataset contents belongs to the original copyright holders.
+
+### Citation Information
+
+If you use any of the datasets, models or code modules, please cite the following paper:
+
+```
+@misc{https://doi.org/10.48550/arxiv.2204.08776,
+  doi = {10.48550/ARXIV.2204.08776},
+  
+  url = {https://arxiv.org/abs/2304.13005},
+  
+  author = {Aggarwal, Divyanshu and Gupta, Vivek and Kunchukuttan, Anoop},
+  
+  keywords = {Computation and Language (cs.CL), Artificial Intelligence (cs.AI), FOS: Computer and information sciences, FOS: Computer and information sciences},
+  
+  title = {IE-SemParse: Evaluating Multilingual Inference for Indian Languages}, 
+  
+  publisher = {arXiv},
+  
+  year = {2022},
+  
+  copyright = {Creative Commons Attribution 4.0 International}
+}
+```
+
+<!-- ### Contributions -->