Natalia V. Loukachevitch, E. Artemova, Tatiana Batura, Pavel Braslavski, Ilia Denisov, V. Ivanov, S. Manandhar, Alexander Pugachev, E. Tutubalina
{"title":"NEREL:一个带有嵌套命名实体、关系和事件的俄语数据集","authors":"Natalia V. Loukachevitch, E. Artemova, Tatiana Batura, Pavel Braslavski, Ilia Denisov, V. Ivanov, S. Manandhar, Alexander Pugachev, E. Tutubalina","doi":"10.26615/978-954-452-072-4_100","DOIUrl":null,"url":null,"abstract":"In this paper, we present NEREL, 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. The NEREL collection is available via https://github.com/nerel-ds/NEREL.","PeriodicalId":284493,"journal":{"name":"Recent Advances in Natural Language Processing","volume":"116 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2021-08-30","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"14","resultStr":"{\"title\":\"NEREL: A Russian Dataset with Nested Named Entities, Relations and Events\",\"authors\":\"Natalia V. Loukachevitch, E. Artemova, Tatiana Batura, Pavel Braslavski, Ilia Denisov, V. Ivanov, S. Manandhar, Alexander Pugachev, E. Tutubalina\",\"doi\":\"10.26615/978-954-452-072-4_100\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"In this paper, we present NEREL, 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. The NEREL collection is available via https://github.com/nerel-ds/NEREL.\",\"PeriodicalId\":284493,\"journal\":{\"name\":\"Recent Advances in Natural Language Processing\",\"volume\":\"116 1\",\"pages\":\"0\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2021-08-30\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"14\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"Recent Advances in Natural Language Processing\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.26615/978-954-452-072-4_100\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"Recent Advances in Natural Language Processing","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.26615/978-954-452-072-4_100","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
NEREL: A Russian Dataset with Nested Named Entities, Relations and Events
In this paper, we present NEREL, 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. The NEREL collection is available via https://github.com/nerel-ds/NEREL.