v1.1.0

NEREL.py

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+import datasets
+import json
+
+_NAME = 'NEREL'
+_CITATION = '''
+@article{loukachevitch2021nerel,
+  title={NEREL: A Russian Dataset with Nested Named Entities, Relations and Events},
+  author={Loukachevitch, Natalia and Artemova, Ekaterina and Batura, Tatiana and Braslavski, Pavel and Denisov, Ilia and Ivanov, Vladimir and Manandhar, Suresh and Pugachev, Alexander and Tutubalina, Elena},
+  journal={arXiv preprint arXiv:2108.13112},
+  year={2021}
+}
+'''.strip()
+_DESCRIPTION = 'A Russian Dataset with Nested Named Entities, Relations and Events'
+_HOMEPAGE = 'https://doi.org/10.48550/arXiv.2108.13112'
+_VERSION = '1.1.0'
+
+
+class NERELBuilder(datasets.GeneratorBasedBuilder):
+    _DATA_URLS = {
+        'train': 'data/train.jsonl',
+        'test': f'data/test.jsonl',
+        'dev': f'data/dev.jsonl',
+    }
+    _ENT_TYPES_URLS = {
+        'ent_types': 'ent_types.jsonl'
+    }
+    _REL_TYPES_URLS = {
+        'rel_types': 'rel_types.jsonl'
+    }
+    VERSION = datasets.Version(_VERSION)
+    BUILDER_CONFIGS = [
+        datasets.BuilderConfig('data',
+                               version=VERSION,
+                               description='Data'),
+        datasets.BuilderConfig('ent_types',
+                               version=VERSION,
+                               description='Entity types list'),
+        datasets.BuilderConfig('rel_types',
+                               version=VERSION,
+                               description='Relation 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')),
+                'relations': datasets.Sequence(datasets.Value('string')),
+                'links': datasets.Sequence(datasets.Value('string'))
+            })
+        elif self.config.name == 'ent_types':
+            features = datasets.Features({
+                'type': datasets.Value('string'),
+                'link': datasets.Value('string')
+            })
+        else:
+            features = datasets.Features({
+                'type': datasets.Value('string'),
+                'arg1': datasets.Sequence(datasets.Value('string')),
+                'arg2': datasets.Sequence(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']},
+                ),
+            ]
+        elif self.config.name == 'ent_types':
+            files = dl_manager.download(self._ENT_TYPES_URLS)
+            return [
+                datasets.SplitGenerator(
+                    name='ent_types',
+                    gen_kwargs={'filepath': files['ent_types']},
+                )
+            ]
+        else:
+            files = dl_manager.download(self._REL_TYPES_URLS)
+            return [
+                datasets.SplitGenerator(
+                    name='rel_types',
+                    gen_kwargs={'filepath': files['rel_types']},
+                )
+            ]
+
+    def _generate_examples(self, filepath):
+        with open(filepath, encoding='utf-8') as f:
+            for i, line in enumerate(f):
+                yield i, json.loads(line)

README.md

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+---
+languages:
+- ru
+multilinguality:
+- monolingual
+pretty_name: NEREL
+task_categories:
+- structure-prediction
+task_ids:
+- named-entity-recognition
+---
+
+# NEREL dataset
+
+## Table of Contents
+- [Dataset Description](#dataset-description)
+- [Dataset Structure](#dataset-structure)
+- [Citation Information](#citation-information)
+- [Contacts](#contacts)
+
+## Dataset Description
+NEREL dataset (https://doi.org/10.48550/arXiv.2108.13112) is
+a Russian dataset for named entity recognition and relation extraction.
+NEREL is significantly larger than existing Russian datasets:
+to date it contains 56K annotated named entities and 39K annotated relations.
+Its important difference from previous datasets is annotation of nested named
+entities, as well as relations within nested entities and at the discourse
+level. NEREL can facilitate development of novel models that can extract
+relations between nested named entities, as well as relations on both sentence
+and document levels. NEREL also contains the annotation of events involving
+named entities and their roles in the events.
+
+You can see full entity types list in a subset "ent_types"
+and full list of relation types in a subset "rel_types".
+
+## Dataset Structure
+There are three "configs" or "subsets" of the dataset.
+
+Using 
+`load_dataset('MalakhovIlya/NEREL', 'ent_types')['ent_types']` 
+you can download list of entity types (
+Dataset({features: ['type', 'link']})
+) where "link" is a knowledge base name used in entity linking task.
+ 
+Using 
+`load_dataset('MalakhovIlya/NEREL', 'rel_types')['rel_types']` 
+you can download list of entity types (
+Dataset({features: ['type', 'arg1', 'arg2']})
+) where "arg1" and "arg2" are lists of entity types that can take part in such
+"type" of relation. \<ENTITY> stands for any type.
+
+Using 
+`load_dataset('MalakhovIlya/NEREL', 'data')` or `load_dataset('MalakhovIlya/NEREL')`
+you can download the data itself, 
+DatasetDict with 3 splits: "train", "test" and "dev".
+Each of them contains text document with annotated entities, relations and
+links.
+
+"entities" are used in named-entity recognition task (see https://en.wikipedia.org/wiki/Named-entity_recognition).  
+"relations" are used in relationship extraction task (see https://en.wikipedia.org/wiki/Relationship_extraction).  
+"links" are used in entity linking task (see https://en.wikipedia.org/wiki/Entity_linking)
+
+Each entity is represented by a string of the following format:  
+`"<id>\t<type> <start> <stop>\t<text>"`, where  
+`<id>` is an entity id,  
+`<type>` is one of entity types,  
+`<start>` is a position of the first symbol of entity in text,  
+`<stop>` is the last symbol position in text +1.
+
+Each relation is represented by a string of the following format:  
+`"<id>\t<type> Arg1:<arg1_id> Arg2:<arg2_id>"`, where  
+`<id>` is a relation id,  
+`<arg1_id>` and `<arg2_id>` are entity ids.
+
+Each link is represented by a string of the following format:  
+`"<id>\tReference <ent_id> <link>\t<text>"`, where  
+`<id>` is a link id,  
+`<ent_id>` is an entity id,  
+`<link>` is a reference to knowledge base entity (example: "Wikidata:Q1879675" if link exists, else "Wikidata:NULL"),  
+`<text>` is a name of entity in knowledge base if link exists, else empty string.
+
+## Citation Information
+@article{loukachevitch2021nerel,  
+    title={NEREL: A Russian Dataset with Nested Named Entities, Relations and Events},  
+    author={Loukachevitch, Natalia and Artemova, Ekaterina and Batura, Tatiana and Braslavski, Pavel and Denisov, Ilia and Ivanov, Vladimir and Manandhar, Suresh and Pugachev, Alexander and Tutubalina, Elena},  
+    journal={arXiv preprint arXiv:2108.13112},  
+    year={2021}  
+}
+
+## Contacts
+Malakhov Ilya  
+Telegram - https://t.me/noname_4710

ent_types.jsonl

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+{"type": "AGE", "link": ""}
+{"type": "AWARD", "link": "<NORM>:Wikidata"}
+{"type": "CITY", "link": "<NORM>:Wikidata"}
+{"type": "COUNTRY", "link": "<NORM>:Wikidata"}
+{"type": "CRIME", "link": ""}
+{"type": "DATE", "link": ""}
+{"type": "DISEASE", "link": "<NORM>:Wikidata"}
+{"type": "DISTRICT", "link": "<NORM>:Wikidata"}
+{"type": "EVENT", "link": "<NORM>:Wikidata"}
+{"type": "FACILITY", "link": "<NORM>:Wikidata"}
+{"type": "FAMILY", "link": ""}
+{"type": "IDEOLOGY", "link": "<NORM>:Wikidata"}
+{"type": "LANGUAGE", "link": "<NORM>:Wikidata"}
+{"type": "LAW", "link": "<NORM>:Wikidata"}
+{"type": "LOCATION", "link": "<NORM>:Wikidata"}
+{"type": "MONEY", "link": ""}
+{"type": "NATIONALITY", "link": "<NORM>:Wikidata"}
+{"type": "NUMBER", "link": ""}
+{"type": "ORDINAL", "link": ""}
+{"type": "ORGANIZATION", "link": "<NORM>:Wikidata"}
+{"type": "PENALTY", "link": ""}
+{"type": "PERCENT", "link": ""}
+{"type": "PERSON", "link": "<NORM>:Wikidata"}
+{"type": "PRODUCT", "link": "<NORM>:Wikidata"}
+{"type": "PROFESSION", "link": "<NORM>:Wikidata"}
+{"type": "RELIGION", "link": "<NORM>:Wikidata"}
+{"type": "STATE_OR_PROVINCE", "link": "<NORM>:Wikidata"}
+{"type": "TIME", "link": ""}
+{"type": "WORK_OF_ART", "link": "<NORM>:Wikidata"}

rel_types.jsonl

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+{"type": "ABBREVIATION", "arg1": ["<ENTITY>"], "arg2": ["<ENTITY>"]}
+{"type": "KNOWS", "arg1": ["PERSON", "PROFESSION"], "arg2": ["<ENTITY>"]}
+{"type": "AGE_IS", "arg1": ["<ENTITY>"], "arg2": ["AGE"]}
+{"type": "AGE_DIED_AT", "arg1": ["PERSON", "PROFESSION"], "arg2": ["AGE"]}
+{"type": "ALTERNATIVE_NAME", "arg1": ["<ENTITY>"], "arg2": ["<ENTITY>"]}
+{"type": "AWARDED_WITH", "arg1": ["PERSON", "PROFESSION", "ORGANIZATION", "WORK_OF_ART", "NATIONALITY"], "arg2": ["AWARD"]}
+{"type": "PLACE_OF_BIRTH", "arg1": ["PERSON", "PROFESSION"], "arg2": ["CITY", "COUNTRY", "DISTRICT", "FACILITY", "LOCATION", "STATE_OR_PROVINCE"]}
+{"type": "CAUSE_OF_DEATH", "arg1": ["PERSON", "PROFESSION", "NATIONALITY"], "arg2": ["DISEASE", "EVENT"]}
+{"type": "DATE_DEFUNCT_IN", "arg1": ["CITY", "COUNTRY", "DISTRICT", "FACILITY", "EVENT", "ORGANIZATION", "STATE_OR_PROVINCE", "WORK_OF_ART"], "arg2": ["DATE"]}
+{"type": "DATE_FOUNDED_IN", "arg1": ["CITY", "COUNTRY", "DISTRICT", "FACILITY", "EVENT", "LOCATION", "ORGANIZATION", "STATE_OR_PROVINCE", "WORK_OF_ART"], "arg2": ["DATE"]}
+{"type": "DATE_OF_BIRTH", "arg1": ["PERSON", "PROFESSION"], "arg2": ["DATE"]}
+{"type": "DATE_OF_CREATION", "arg1": ["WORK_OF_ART", "LAW", "AWARD", "PRODUCT"], "arg2": ["DATE"]}
+{"type": "DATE_OF_DEATH", "arg1": ["PERSON", "PROFESSION", "NATIONALITY"], "arg2": ["DATE"]}
+{"type": "POINT_IN_TIME", "arg1": ["EVENT", "PENALTY", "CRIME", "WORK_OF_ART", "AWARD", "PRODUCT"], "arg2": ["DATE", "TIME"]}
+{"type": "PLACE_OF_DEATH", "arg1": ["PERSON", "PROFESSION", "NATIONALITY"], "arg2": ["CITY", "COUNTRY", "DISTRICT", "FACILITY", "LOCATION", "STATE_OR_PROVINCE"]}
+{"type": "FOUNDED_BY", "arg1": ["CITY", "COUNTRY", "DISTRICT", "FACILITY", "EVENT", "LOCATION", "ORGANIZATION", "STATE_OR_PROVINCE", "PROFESSION"], "arg2": ["CITY", "COUNTRY", "DISTRICT", "FACILITY", "EVENT", "LOCATION", "ORGANIZATION", "PERSON", "PROFESSION", "STATE_OR_PROVINCE", "FAMILY"]}
+{"type": "HEADQUARTERED_IN", "arg1": ["ORGANIZATION"], "arg2": ["LOCATION", "CITY", "COUNTRY", "DISTRICT", "STATE_OR_PROVINCE", "FACILITY"]}
+{"type": "IDEOLOGY_OF", "arg1": ["PERSON", "ORGANIZATION", "PROFESSION", "COUNTRY", "FACILITY", "NATIONALITY", "EVENT"], "arg2": ["IDEOLOGY"]}
+{"type": "LOCATED_IN", "arg1": ["PERSON", "PROFESSION", "CITY", "COUNTRY", "DISTRICT", "FACILITY", "LOCATION", "ORGANIZATION", "PRODUCT", "STATE_OR_PROVINCE", "WORK_OF_ART"], "arg2": ["CITY", "COUNTRY", "DISTRICT", "FACILITY", "LOCATION", "ORGANIZATION", "STATE_OR_PROVINCE"]}
+{"type": "SPOUSE", "arg1": ["PERSON", "PROFESSION"], "arg2": ["PERSON", "PROFESSION"]}
+{"type": "MEDICAL_CONDITION", "arg1": ["PERSON", "PROFESSION"], "arg2": ["DISEASE"]}
+{"type": "MEMBER_OF", "arg1": ["PERSON", "PROFESSION", "ORGANIZATION", "COUNTRY"], "arg2": ["ORGANIZATION", "IDEOLOGY", "COUNTRY", "FAMILY"]}
+{"type": "ORGANIZES", "arg1": ["CITY", "COUNTRY", "DISTRICT", "ORGANIZATION", "PERSON", "PROFESSION", "STATE_OR_PROVINCE"], "arg2": ["EVENT"]}
+{"type": "ORIGINS_FROM", "arg1": ["<ENTITY>"], "arg2": ["<ENTITY>"]}
+{"type": "OWNER_OF", "arg1": ["<ENTITY>"], "arg2": ["<ENTITY>"]}
+{"type": "PARENT_OF", "arg1": ["PERSON", "PROFESSION", "NATIONALITY"], "arg2": ["PERSON", "PROFESSION", "NATIONALITY"]}
+{"type": "PLACE_RESIDES_IN", "arg1": ["PERSON", "PROFESSION", "NATIONALITY", "FAMILY"], "arg2": ["CITY", "COUNTRY", "DISTRICT", "FACILITY", "LOCATION", "STATE_OR_PROVINCE"]}
+{"type": "PRICE_OF", "arg1": ["<ENTITY>"], "arg2": ["MONEY"]}
+{"type": "PRODUCES", "arg1": ["CITY", "COUNTRY", "DISTRICT", "ORGANIZATION", "PERSON", "PROFESSION", "STATE_OR_PROVINCE"], "arg2": ["<ENTITY>"]}
+{"type": "RELATIVE", "arg1": ["<ENTITY>"], "arg2": ["<ENTITY>"]}
+{"type": "RELIGION_OF", "arg1": ["PERSON", "ORGANIZATION", "PROFESSION", "COUNTRY", "FACILITY", "NATIONALITY", "EVENT"], "arg2": ["RELIGION"]}
+{"type": "SCHOOLS_ATTENDED", "arg1": ["PERSON", "PROFESSION", "NATIONALITY"], "arg2": ["ORGANIZATION"]}
+{"type": "SIBLING", "arg1": ["PERSON", "PROFESSION"], "arg2": ["PERSON", "PROFESSION"]}
+{"type": "SUBEVENT_OF", "arg1": ["EVENT"], "arg2": ["EVENT"]}
+{"type": "SUBORDINATE_OF", "arg1": ["PERSON", "PROFESSION"], "arg2": ["PERSON", "PROFESSION"]}
+{"type": "TAKES_PLACE_IN", "arg1": ["EVENT", "CRIME", "PENALTY"], "arg2": ["CITY", "COUNTRY", "DISTRICT", "ORGANIZATION", "STATE_OR_PROVINCE", "FACILITY", "LOCATION"]}
+{"type": "WORKPLACE", "arg1": ["PERSON", "PROFESSION"], "arg2": ["CITY", "COUNTRY", "DISTRICT", "FACILITY", "EVENT", "LOCATION", "IDEOLOGY", "ORGANIZATION", "STATE_OR_PROVINCE"]}
+{"type": "WORKS_AS", "arg1": ["PERSON"], "arg2": ["PROFESSION"]}
+{"type": "START_TIME", "arg1": ["EVENT", "PENALTY", "CRIME", "WORK_OF_ART"], "arg2": ["DATE", "TIME"]}
+{"type": "END_TIME", "arg1": ["EVENT", "PENALTY", "CRIME", "WORK_OF_ART"], "arg2": ["DATE", "TIME"]}
+{"type": "CONVICTED_OF", "arg1": ["PERSON", "PROFESSION", "ORGANIZATION", "FAMILY", "NATIONALITY", "COUNTRY"], "arg2": ["CRIME"]}
+{"type": "PENALIZED_AS", "arg1": ["PERSON", "PROFESSION", "ORGANIZATION", "FAMILY", "NATIONALITY", "COUNTRY"], "arg2": ["PENALTY"]}
+{"type": "PART_OF", "arg1": ["ORGANIZATION", "WORK_OF_ART", "LAW", "FACILITY", "PRODUCT", "AWARD"], "arg2": ["ORGANIZATION", "WORK_OF_ART", "LAW", "FACILITY", "PRODUCT", "AWARD"]}
+{"type": "HAS_CAUSE", "arg1": ["EVENT", "CRIME", "PENALTY", "AWARD", "DISEASE"], "arg2": ["EVENT", "CRIME", "PENALTY", "LAW", "DISEASE"]}
+{"type": "AGENT", "arg1": ["PERSON", "PROFESSION", "ORGANIZATION", "CITY", "COUNTRY", "STATE_OR_PROVINCE", "FAMILY", "NATIONALITY", "IDEOLOGY", "RELIGION"], "arg2": ["EVENT"]}
+{"type": "PARTICIPANT_IN", "arg1": ["PERSON", "PROFESSION", "ORGANIZATION", "CITY", "COUNTRY", "STATE_OR_PROVINCE", "FACILITY", "AWARD", "WORK_OF_ART", "FAMILY", "NATIONALITY", "IDEOLOGY", "RELIGION", "NATIONALITY"], "arg2": ["EVENT", "WORK_OF_ART", "CRIME", "PENALTY"]}
+{"type": "INANIMATE_INVOLVED", "arg1": ["PERSON", "PRODUCT", "FACILITY", "AWARD", "WORK_OF_ART", "LAW", "MONEY"], "arg2": ["EVENT", "WORK_OF_ART", "CRIME", "PENALTY"]}
+{"type": "EXPENDITURE", "arg1": ["PERSON", "PROFESSION", "CITY", "COUNTRY", "DISTRICT", "ORGANIZATION", "FAMILY", "STATE_OR_PROVINCE", "NATIONALITY"], "arg2": ["MONEY"]}
+{"type": "INCOME", "arg1": ["PERSON", "PROFESSION", "CITY", "COUNTRY", "DISTRICT", "ORGANIZATION", "FAMILY", "STATE_OR_PROVINCE", "NATIONALITY"], "arg2": ["MONEY"]}