Update files from the datasets library (from 1.2.0)

Release notes: https://github.com/huggingface/datasets/releases/tag/1.2.0

.gitattributes

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+*.arrow filter=lfs diff=lfs merge=lfs -text
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README.md

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+---
+annotations_creators:
+- expert-generated
+language_creators:
+- expert-generated
+languages:
+- fi
+licenses:
+- cc-by-nc-sa-4-0
+multilinguality:
+- monolingual
+size_categories:
+- 10K<n<100K
+source_datasets:
+- original
+task_categories:
+- structure-prediction
+task_ids:
+- named-entity-recognition
+---
+
+# Dataset Card Creation Guide
+
+## Table of Contents
+- [Dataset Description](#dataset-description)
+  - [Dataset Summary](#dataset-summary)
+  - [Supported Tasks](#supported-tasks-and-leaderboards)
+  - [Languages](#languages)
+- [Dataset Structure](#dataset-structure)
+  - [Data Instances](#data-instances)
+  - [Data Fields](#data-instances)
+  - [Data Splits](#data-instances)
+- [Dataset Creation](#dataset-creation)
+  - [Curation Rationale](#curation-rationale)
+  - [Source Data](#source-data)
+  - [Annotations](#annotations)
+  - [Personal and Sensitive Information](#personal-and-sensitive-information)
+- [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)
+- [Additional Information](#additional-information)
+  - [Dataset Curators](#dataset-curators)
+  - [Licensing Information](#licensing-information)
+  - [Citation Information](#citation-information)
+
+## Dataset Description
+
+- **Homepage:** https://turkunlp.org/fin-ner.html
+- **Repository:** https://github.com/TurkuNLP/turku-ner-corpus/
+- **Paper:** https://www.aclweb.org/anthology/2020.lrec-1.567/
+- **Leaderboard:** [If the dataset supports an active leaderboard, add link here]()
+- **Point of Contact:** {jouni.a.luoma,mhtoin,maria.h.pyykonen,mavela,sampo.pyysalo}@utu.f
+
+### Dataset Summary
+
+[More Information Needed]
+
+### Supported Tasks and Leaderboards
+
+[More Information Needed]
+
+### Languages
+
+[More Information Needed]
+
+## Dataset Structure
+
+### Data Instances
+
+[More Information Needed]
+
+### Data Fields
+
+[More Information Needed]
+
+### Data Splits
+
+[More Information Needed]
+## Dataset Creation
+
+### Curation Rationale
+
+[More Information Needed]
+
+### Source Data
+
+[More Information Needed]
+
+#### Initial Data Collection and Normalization
+
+[More Information Needed]
+
+#### Who are the source language producers?
+
+[More Information Needed]
+
+### Annotations
+
+[More Information Needed]
+
+#### Annotation process
+
+[More Information Needed]
+
+#### Who are the annotators?
+
+[More Information Needed]
+
+### Personal and Sensitive Information
+
+[More Information Needed]
+
+## Considerations for Using the Data
+
+### Social Impact of Dataset
+
+[More Information Needed]
+
+### Discussion of Biases
+
+[More Information Needed]
+
+### Other Known Limitations
+
+[More Information Needed]
+
+## Additional Information
+
+### Dataset Curators
+
+[More Information Needed]
+
+### Licensing Information
+
+[More Information Needed]
+
+### Citation Information
+
+[More Information Needed]

dataset_infos.json

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+{"default": {"description": "An open, broad-coverage corpus for Finnish named entity recognition presented in Luoma et al. (2020) A Broad-coverage Corpus for Finnish Named Entity Recognition.\n", "citation": "@inproceedings{luoma-etal-2020-broad,\ntitle = \"A Broad-coverage Corpus for {F}innish Named Entity Recognition\",\nauthor = {Luoma, Jouni and Oinonen, Miika and Pyyk{\"o}nen, Maria and Laippala, Veronika and Pyysalo, Sampo},\nbooktitle = \"Proceedings of The 12th Language Resources and Evaluation Conference\",\nyear = \"2020\",\nurl = \"https://www.aclweb.org/anthology/2020.lrec-1.567\",\npages = \"4615--4624\",\n}\n", "homepage": "https://github.com/klintan/swedish-ner-corpus", "license": "", "features": {"id": {"dtype": "string", "id": null, "_type": "Value"}, "tokens": {"feature": {"dtype": "string", "id": null, "_type": "Value"}, "length": -1, "id": null, "_type": "Sequence"}, "ner_tags": {"feature": {"num_classes": 13, "names": ["B-DATE", "B-EVENT", "B-LOC", "B-ORG", "B-PER", "B-PRO", "I-DATE", "I-EVENT", "I-LOC", "I-ORG", "I-PER", "I-PRO", "O"], "names_file": null, "id": null, "_type": "ClassLabel"}, "length": -1, "id": null, "_type": "Sequence"}}, "post_processed": null, "supervised_keys": null, "builder_name": "turku_ner_corpus", "config_name": "default", "version": {"version_str": "1.0.0", "description": null, "major": 1, "minor": 0, "patch": 0}, "splits": {"train": {"name": "train", "num_bytes": 3257447, "num_examples": 12217, "dataset_name": "turku_ner_corpus"}, "validation": {"name": "validation", "num_bytes": 364223, "num_examples": 1364, "dataset_name": "turku_ner_corpus"}, "test": {"name": "test", "num_bytes": 416644, "num_examples": 1555, "dataset_name": "turku_ner_corpus"}}, "download_checksums": {"https://github.com/TurkuNLP/turku-ner-corpus/archive/v1.0.tar.gz": {"num_bytes": 1659911, "checksum": "c02dbca228431b17d90acfa67ad722cf81828b263a791de79fc578c478b1fb35"}}, "download_size": 1659911, "post_processing_size": null, "dataset_size": 4038314, "size_in_bytes": 5698225}}

dummy/1.0.0/dummy_data.zip

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+version https://git-lfs.github.com/spec/v1
+oid sha256:e9ad7c95fc1a8a70913639c16f151d05c5edb893f26554059a88fd7d089f9c37
+size 1911

turku_ner_corpus.py

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+# coding=utf-8
+# Copyright 2020 HuggingFace Datasets Authors.
+#
+# Licensed under the Apache License, Version 2.0 (the "License");
+# you may not use this file except in compliance with the License.
+# You may obtain a copy of the License at
+#
+#     http://www.apache.org/licenses/LICENSE-2.0
+#
+# Unless required by applicable law or agreed to in writing, software
+# distributed under the License is distributed on an "AS IS" BASIS,
+# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
+# See the License for the specific language governing permissions and
+# limitations under the License.
+
+# Lint as: python3
+import os
+
+import datasets
+
+
+_DESCRIPTION = """\
+An open, broad-coverage corpus for Finnish named entity recognition presented in Luoma et al. (2020) A Broad-coverage Corpus for Finnish Named Entity Recognition.
+"""
+_HOMEPAGE_URL = "https://turkunlp.org/fin-ner.html"
+_URL = "https://github.com/TurkuNLP/turku-ner-corpus/archive/v1.0.tar.gz"
+_CITATION = """\
+@inproceedings{luoma-etal-2020-broad,
+title = "A Broad-coverage Corpus for {F}innish Named Entity Recognition",
+author = {Luoma, Jouni and Oinonen, Miika and Pyyk{\"o}nen, Maria and Laippala, Veronika and Pyysalo, Sampo},
+booktitle = "Proceedings of The 12th Language Resources and Evaluation Conference",
+year = "2020",
+url = "https://www.aclweb.org/anthology/2020.lrec-1.567",
+pages = "4615--4624",
+}
+"""
+
+
+class TurkuNERCorpus(datasets.GeneratorBasedBuilder):
+    VERSION = datasets.Version("1.0.0")
+
+    def _info(self):
+        return datasets.DatasetInfo(
+            description=_DESCRIPTION,
+            features=datasets.Features(
+                {
+                    "id": datasets.Value("string"),
+                    "tokens": datasets.Sequence(datasets.Value("string")),
+                    "ner_tags": datasets.Sequence(
+                        datasets.features.ClassLabel(
+                            names=[
+                                "B-DATE",
+                                "B-EVENT",
+                                "B-LOC",
+                                "B-ORG",
+                                "B-PER",
+                                "B-PRO",
+                                "I-DATE",
+                                "I-EVENT",
+                                "I-LOC",
+                                "I-ORG",
+                                "I-PER",
+                                "I-PRO",
+                                "O",
+                            ]
+                        )
+                    ),
+                },
+            ),
+            supervised_keys=None,
+            homepage=_HOMEPAGE_URL,
+            citation=_CITATION,
+        )
+
+    def _split_generators(self, dl_manager):
+        path = dl_manager.download_and_extract(_URL)
+        return [
+            datasets.SplitGenerator(
+                name=datasets.Split.TRAIN,
+                gen_kwargs={"data_path": path, "data_type": "train"},
+            ),
+            datasets.SplitGenerator(
+                name=datasets.Split.VALIDATION,
+                gen_kwargs={"data_path": path, "data_type": "valid"},
+            ),
+            datasets.SplitGenerator(
+                name=datasets.Split.TEST,
+                gen_kwargs={"data_path": path, "data_type": "test"},
+            ),
+        ]
+
+    def _generate_examples(self, data_path, data_type):
+        if data_type == "train":
+            data_path = os.path.join(data_path, "turku-ner-corpus-1.0/data/conll/train.tsv")
+        elif data_type == "valid":
+            data_path = os.path.join(data_path, "turku-ner-corpus-1.0/data/conll/dev.tsv")
+        elif data_type == "test":
+            data_path = os.path.join(data_path, "turku-ner-corpus-1.0/data/conll/test.tsv")
+        else:
+            raise Exception("data_type not understood")
+
+        sentence_counter = 0
+        with open(data_path, encoding="utf-8") as f:
+            current_words = []
+            current_labels = []
+            for row in f:
+                row = row.rstrip()
+                row_split = row.split("\t")
+                if len(row_split) == 2:
+                    token, label = row_split
+                    current_words.append(token)
+                    current_labels.append(label)
+                else:
+                    if not current_words:
+                        continue
+                    assert len(current_words) == len(current_labels), "word len doesnt match label length"
+                    sentence = (
+                        sentence_counter,
+                        {
+                            "id": str(sentence_counter),
+                            "tokens": current_words,
+                            "ner_tags": current_labels,
+                        },
+                    )
+                    sentence_counter += 1
+                    current_words = []
+                    current_labels = []
+                    yield sentence
+
+            # if something remains:
+            if current_words:
+                sentence = (
+                    sentence_counter,
+                    {
+                        "id": str(sentence_counter),
+                        "tokens": current_words,
+                        "ner_tags": current_labels,
+                    },
+                )
+                yield sentence