add script and update readme

README.md

@@ -1,3 +1,60 @@
 ---
 license: cc-by-sa-4.0
+task_categories:
+- text-classification
+language:
+- de
+- it
+- cs
+pretty_name: MERLIN Written Learner Corpus for Czech, German, Italian 1.1.
+size_categories:
+- 1K<n<10K
 ---
+
+# Dataset Card for MERLIN
+
+The MERLIN corpus is a written learner corpus for Czech, German, and Italian that has been
+designed to illustrate the Common European Framework of Reference for Languages (CEFR) with
+authentic learner data. The corpus contains learner texts produced in standardized language
+certifications covering CEFR levels A1-C1. The MERLIN annotation scheme includes a wide
+range of language characteristics that provide researchers with concrete examples of learner
+performance and progress across multiple proficiency levels.
+
+## Dataset Details
+
+### Dataset Description
+
+The MERLIN corpus contains 2,286 texts for learners of Italian, German and Czech that were taken from written examinations of acknowledged test institutions. The exams aim to test knowledge across the levels A1-C1 of the Common European Framework of Reference (CEFR).
+
+- **Homepage :** https://merlin-platform.eu/
+- **Funded by :** The MERLIN project was funded from 2012 until 2014 by the EU Lifelong Learning Programme under project number 518989-LLP-1-2011-1-DE-KA2-KA2MP.
+- **Shared by :** Since 2018, corpus data are available through the CLARIN network.
+- **Language(s) (NLP):** Czech, German and Italian
+- **License:** Creative Commons - Attribution-ShareAlike 4.0 International (CC BY-SA 4.0)
+
+### Dataset Sources
+
+- **Repository:** https://clarin.eurac.edu/repository/xmlui/handle/20.500.12124/6
+- **Paper:** Wisniewski, Katrin; Abel, Andrea; Vodičková, Kateřina; et al., 2018, 
+  MERLIN Written Learner Corpus for Czech, German, Italian 1.1, Eurac Research CLARIN Centre, 
+  http://hdl.handle.net/20.500.12124/6.
+
+## Uses
+
+- Teachers and material writers
+- Curriculum design and course planning
+- Language testing
+
+For more details and practicla examples, see [use cases](https://www.merlin-platform.eu/C_teacher.php).
+
+## Citation
+
+**BibTeX:**
+
+ @misc{20.500.12124/6,
+ title = {{MERLIN} Written Learner Corpus for Czech, German, Italian 1.1},
+ author = {Wisniewski, Katrin and Abel, Andrea and Vodi{\v c}kov{\'a}, Kate{\v r}ina and Plassmann, Sybille and Meurers, Detmar and Woldt, Claudia and Sch{\"o}ne, Karin and Blaschitz, Verena and Lyding, Verena and Nicolas, Lionel and Vettori, Chiara and Pe{\v c}en{\'y}, Pavel and Hana, Jirka and {\v C}urdov{\'a}, Veronika and {\v S}tindlov{\'a}, Barbora and Klein, Gudrun and Lauppe, Louise and Boyd, Adriane and Bykh, Serhiy and Krivanek, Julia},
+ url = {http://hdl.handle.net/20.500.12124/6},
+ note = {Eurac Research {CLARIN} Centre},
+ copyright = {Creative Commons - Attribution-{ShareAlike} 4.0 International ({CC} {BY}-{SA} 4.0)},
+ year = {2018} }

merlin.py

@@ -0,0 +1,150 @@
+# Copyright 2020 The HuggingFace Datasets Authors and the current dataset script contributor.
+#
+# 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.
+"""MERLIN Written Learner Corpus for Czech, German, Italian 1.1."""
+
+
+import csv
+import json
+import os
+
+import datasets
+
+_CITATION = """\
+@misc{20.500.12124/6,
+ title = {{MERLIN} Written Learner Corpus for Czech, German, Italian 1.1},
+ author = {Wisniewski, Katrin and Abel, Andrea and Vodi{\v c}kov{\'a}, Kate{\v r}ina and Plassmann,
+ Sybille and Meurers, Detmar and Woldt, Claudia and Sch{\"o}ne, Karin and Blaschitz, Verena and Lyding,
+ Verena and Nicolas, Lionel and Vettori, Chiara and Pe{\v c}en{\'y}, Pavel and Hana, Jirka and
+ {\v C}urdov{\'a}, Veronika and {\v S}tindlov{\'a}, Barbora and Klein, Gudrun and Lauppe, Louise and Boyd,
+ Adriane and Bykh, Serhiy and Krivanek, Julia},
+ url = {http://hdl.handle.net/20.500.12124/6},
+ note = {Eurac Research {CLARIN} Centre},
+ copyright = {Creative Commons - Attribution-{ShareAlike} 4.0 International ({CC} {BY}-{SA} 4.0)},
+ year = {2018} }
+"""
+
+_DESCRIPTION = """\
+The MERLIN corpus is a written learner corpus for Czech, German, and Italian that has been
+designed to illustrate the Common European Framework of Reference for Languages (CEFR) with
+authentic learner data. The corpus contains learner texts produced in standardized language
+certifications covering CEFR levels A1-C1. The MERLIN annotation scheme includes a wide
+range of language characteristics that provide researchers with concrete examples of learner
+performance and progress across multiple proficiency levels.
+"""
+
+_HOMEPAGE = "https://merlin-platform.eu/"
+
+_LICENSE = "Creative Commons - Attribution-ShareAlike 4.0 International (CC BY-SA 4.0)"
+
+_URLS = {
+    "multilingual": "https://clarin.eurac.edu/repository/xmlui/bitstream/handle/20.500.12124/6/merlin-text-v1.1.zip",
+    "german": "https://clarin.eurac.edu/repository/xmlui/bitstream/handle/20.500.12124/6/merlin-text-v1.1.zip",
+    "italian": "https://clarin.eurac.edu/repository/xmlui/bitstream/handle/20.500.12124/6/merlin-text-v1.1.zip",
+    "czech": "https://clarin.eurac.edu/repository/xmlui/bitstream/handle/20.500.12124/6/merlin-text-v1.1.zip",
+}
+
+class MerlinDataset(datasets.GeneratorBasedBuilder):
+    """Merlin dataset including three languages."""
+
+    VERSION = datasets.Version("1.1.0")
+
+    BUILDER_CONFIGS = [
+        datasets.BuilderConfig(name="multilingual", version=VERSION, description="Merlin dataset including three languages."),
+        datasets.BuilderConfig(name="german", version=VERSION, description="Merlin dataset German."),
+        datasets.BuilderConfig(name="italian", version=VERSION, description="Merlin dataset Italian."),
+        datasets.BuilderConfig(name="czech", version=VERSION, description="Merlin dataset Czech."),
+    ]
+
+
+    def _info(self):
+        features = datasets.Features(
+            {
+                "author": datasets.Value("string"),
+                "language": datasets.ClassLabel(num_classes=3, names=["Czech", "German", "Italian"]),
+                "level": datasets.ClassLabel(num_classes=6, names=['A1', 'A2', 'B1', 'B2', 'C1', 'C2']),
+                "level_grammar": datasets.ClassLabel(num_classes=6, names=['A1', 'A2', 'B1', 'B2', 'C1', 'C2']),
+                "level_ortography":  datasets.ClassLabel(num_classes=6, names=['A1', 'A2', 'B1', 'B2', 'C1', 'C2']),
+                "level_vocabulary_range": datasets.ClassLabel(num_classes=6, names=['A1', 'A2', 'B1', 'B2', 'C1', 'C2']),
+                "level_vocabulary_control": datasets.ClassLabel(num_classes=6, names=['A1', 'A2', 'B1', 'B2', 'C1', 'C2']),
+                "level_coherence":  datasets.ClassLabel(num_classes=6, names=['A1', 'A2', 'B1', 'B2', 'C1', 'C2']),
+                "level_appropriateness": datasets.ClassLabel(num_classes=6, names=['A1', 'A2', 'B1', 'B2', 'C1', 'C2']),
+                "text": datasets.Value("string"),
+                "text_target": datasets.Value("string"),
+            }
+        )
+
+        return datasets.DatasetInfo(
+            description=_DESCRIPTION,
+            features=features,
+            homepage=_HOMEPAGE,
+            license=_LICENSE,
+            citation=_CITATION,
+        )
+
+    def _split_generators(self, dl_manager):
+        urls = _URLS[self.config.name]
+        data_dir = dl_manager.download_and_extract(urls)
+        filepath = os.path.join(data_dir, "merlin-text-v1.1/meta_ltext_THs")
+        if self.config.name != "multilingual":
+            filepath = os.path.join(filepath, self.config.name)
+        print(f"Genereting split from {filepath}")
+        return [
+            datasets.SplitGenerator(
+                name=datasets.Split.TRAIN,
+                gen_kwargs={
+                    "filepath": filepath,
+                    "split": "train",
+                },
+            ),
+        ]
+
+    def _generate_examples(self, filepath, split):
+        import re
+
+        file_list = []
+        for path, _, files in os.walk(filepath):
+            for file in files:
+                file_list.append(os.path.join(path, file))
+
+        print(f"Reading {len(file_list)} files")
+        # Transform the data
+        for f in file_list:
+            raw_text = open(f, "r").read()
+
+            language = re.findall(r'(Test language: )(.*?)(\n)', raw_text)[0][1]
+            author_id = re.findall(r'(Author ID: )(.*?)(\n)', raw_text)[0][1]
+            level = re.findall(r'(CEFR level of test: )(.*?)(\n)', raw_text)[0][1]
+            level_grammar = re.findall(r'(Grammatical accuracy: )(.*?)(\n)', raw_text)[0][1]
+            level_ortography = re.findall(r'(Orthography: )(.*?)(\n)', raw_text)[0][1]
+            level_vocabulary_range = re.findall(r'(Vocabulary range: )(.*?)(\n)', raw_text)[0][1]
+            level_vocabulary_control = re.findall(r'(Vocabulary control: )(.*?)(\n)', raw_text)[0][1]
+            level_coherence = re.findall(r'(Coherence/Cohesion: )(.*?)(\n)', raw_text)[0][1]
+            level_appropriateness = re.findall(r'(Sociolinguistic appropriateness: )(.*?)(\n)', raw_text)[0][1]
+            text = re.findall(r'(Learner text: \n\n)(.*?)(\n\n----------------\n\n)', raw_text, re.DOTALL)[0][1]
+            text_target = re.findall(r'(Target hypothesis 1: \n\n)(.*?)(\n\n----------------\n\n)', raw_text, re.DOTALL)[0][1]
+
+            id_ = f'{language}_{author_id}'
+            yield id_, {
+                "author": author_id,
+                "language": language,
+                "level": level,
+                "level_grammar": level_grammar,
+                "level_ortography":  level_ortography,
+                "level_vocabulary_range": level_vocabulary_range,
+                "level_vocabulary_control": level_vocabulary_control,
+                "level_coherence": level_coherence,
+                "level_appropriateness": level_appropriateness,
+                "text": text,
+                "text_target": text_target,
+            }