v1.0.0

README.md

@@ -0,0 +1,89 @@
+---
+languages:
+- ru
+multilinguality:
+- monolingual
+pretty_name: RuNNE
+task_categories:
+- structure-prediction
+task_ids:
+- named-entity-recognition
+---
+
+# RuNNE dataset
+
+## Table of Contents
+- [Dataset Description](#dataset-description)
+- [Dataset Structure](#dataset-structure)
+- [Citation Information](#citation-information)
+- [Contacts](#contacts)
+
+## Dataset Description
+Part of NEREL dataset (https://arxiv.org/abs/2108.13112), a Russian dataset
+for named entity recognition and relation extraction, used in RuNNE (2022)
+competition (https://github.com/dialogue-evaluation/RuNNE).
+
+Entities may be nested (see https://arxiv.org/abs/2108.13112).
+
+Entity types list:
+* AGE
+* AWARD
+* CITY
+* COUNTRY
+* CRIME
+* DATE
+* DISEASE
+* DISTRICT
+* EVENT
+* FACILITY
+* FAMILY
+* IDEOLOGY
+* LANGUAGE
+* LAW
+* LOCATION
+* MONEY
+* NATIONALITY
+* NUMBER
+* ORDINAL
+* ORGANIZATION
+* PENALTY
+* PERCENT
+* PERSON
+* PRODUCT
+* PROFESSION
+* RELIGION
+* STATE_OR_PROVINCE
+* TIME
+* WORK_OF_ART
+
+## Dataset Structure
+There are two "configs" or "subsets" of the dataset.  
+Using 
+`load_dataset('MalakhovIlya/RuNNE', 'ent_types')['ent_types']` 
+you can download list of entity types (
+Dataset({
+    features: ['type'],
+    num_rows: 29
+})
+)  
+Using 
+`load_dataset('MalakhovIlya/RuNNE', 'data')` or `load_dataset('MalakhovIlya/RuNNE')`
+you can download the data itself (DatasetDict)
+
+Dataset consists of 3 splits: "train", "test" and "dev". Each of them contains text document. "Train" and "test" splits also contain annotated entities, "dev" doesn't.
+Each entity is represented by a string of the following format: "\<start> \<stop> \<type>", where \<start> is a position of the first symbol of entity in text, \<stop> is the last symbol position in text and \<type> is a one of the aforementioned list of types.
+
+P.S.
+Original NEREL dataset also contains relations, events and linked entities, but they were not added here yet ¯\\\_(ツ)_/¯
+
+## Citation Information
+@article{Artemova2022runne, 
+  title={{RuNNE-2022 Shared Task: Recognizing Nested Named Entities}},
+  author={Artemova, Ekaterina and Zmeev, Maksim and Loukachevitch, Natalia and Rozhkov, Igor and Batura, Tatiana and Braslavski, Pavel and Ivanov, Vladimir and Tutubalina, Elena},
+  journal={Computational Linguistics and Intellectual Technologies: Proceedings of the International Conference "Dialog"},
+  year={2022}
+}
+
+## Contacts
+Malakhov Ilya  
+Telegram - https://t.me/noname_4710

RuNNE.py

@@ -0,0 +1,94 @@
+import datasets
+import json
+
+_NAME = 'RuNNE'
+_CITATION = '''
+@article{Artemova2022runne,
+    title={{RuNNE-2022 Shared Task: Recognizing Nested Named Entities}},
+    author={Artemova, Ekaterina and Zmeev, Maksim and Loukachevitch,
+            Natalia and Rozhkov, Igor and Batura, Tatiana and Braslavski,
+            Pavel and Ivanov, Vladimir and Tutubalina, Elena},
+    journal={Computational Linguistics and Intellectual Technologies:
+             Proceedings of the International Conference "Dialog"},
+    year={2022}
+}
+'''.strip()
+_DESCRIPTION = 'A Russian Dataset with Nested Named Entities'
+_HOMEPAGE = 'https://github.com/dialogue-evaluation/RuNNE'
+_VERSION = '1.0.0'
+
+
+class RuNNEBuilder(datasets.GeneratorBasedBuilder):
+    _DATA_URLS = {
+        'train': 'data/train.jsonl',
+        'test': 'data/test.jsonl',
+        'dev': 'data/dev.jsonl'
+    }
+    _ENTITY_TYPES_URLS = {
+        'ent_types': 'ent_types.txt'
+    }
+    VERSION = datasets.Version(_VERSION)
+    BUILDER_CONFIGS = [
+        datasets.BuilderConfig('data',
+                               version=VERSION,
+                               description='Data'),
+        datasets.BuilderConfig('ent_types',
+                               version=VERSION,
+                               description='Entity types list')
+    ]
+    DEFAULT_CONFIG_NAME = 'data'
+
+    def _info(self) -> datasets.DatasetInfo:
+        if self.config.name == 'data':
+            features = datasets.Features({
+                'id': datasets.Value('int32'),
+                'text': datasets.Value('string'),
+                'entities': datasets.Sequence(datasets.Value('string'))
+            })
+        else:
+            features = datasets.Features({
+                'type': datasets.Value('string')
+            })
+        return datasets.DatasetInfo(
+            description=_DESCRIPTION,
+            features=features,
+            homepage=_HOMEPAGE,
+            citation=_CITATION
+        )
+
+    def _split_generators(self, dl_manager: datasets.DownloadManager):
+        if self.config.name == 'data':
+            files = dl_manager.download(self._DATA_URLS)
+            return [
+                datasets.SplitGenerator(
+                    name=datasets.Split.TRAIN,
+                    gen_kwargs={'filepath': files['train']},
+                ),
+                datasets.SplitGenerator(
+                    name=datasets.Split.TEST,
+                    gen_kwargs={'filepath': files['test']},
+                ),
+                datasets.SplitGenerator(
+                    name='dev',
+                    gen_kwargs={'filepath': files['dev']},
+                ),
+            ]
+        else:
+            files = dl_manager.download(self._ENTITY_TYPES_URLS)
+            return [datasets.SplitGenerator(
+                name='ent_types',
+                gen_kwargs={'filepath': files['ent_types']},
+            )]
+
+    def _generate_examples(self, filepath):
+        if self.config.name == 'data':
+            with open(filepath, encoding='utf-8') as f:
+                for line in f:
+                    doc = json.loads(line)
+                    yield doc['id'], doc
+        else:
+            with open(filepath, encoding='utf-8') as f:
+                for i, line in enumerate(f):
+                    entity_type = line.strip()
+                    if entity_type:
+                        yield i, {'type': entity_type}

ent_types.txt

@@ -0,0 +1,29 @@
+AGE
+AWARD
+CITY
+COUNTRY
+CRIME
+DATE
+DISEASE
+DISTRICT
+EVENT
+FACILITY
+FAMILY
+IDEOLOGY
+LANGUAGE
+LAW
+LOCATION
+MONEY
+NATIONALITY
+NUMBER
+ORDINAL
+ORGANIZATION
+PENALTY
+PERCENT
+PERSON
+PRODUCT
+PROFESSION
+RELIGION
+STATE_OR_PROVINCE
+TIME
+WORK_OF_ART