Work

NNE: A Dataset for Nested Named Entity Recognition in English Newswire

Year: 2019

Type: conference-paper

Abstract: Named entity recognition (NER) is widely used in natural language processing applications and downstream tasks.However, most NER tools target flat annotation from popular datasets, eschewing the semantic information available in nested entity mentions.We describe NNE-a fine-grained, nested named entity dataset over the full Wall Street Journal portion of the Penn Treebank (PTB).Our annotation comprises 279,795 mentions of 114 entity types with up to 6 layers of nesting.We hope the public release of this large dataset for English newswire will encourage development of new techniques for nested NER.

Source: Proceedings of the conference - Association for Computational Linguistics. Meeting

DOI: 10.18653/v1/p19-1510

Authors: Nicky Ringland, Xiang Dai, Ben Hachey, Sarvnaz Karimi, Cecile Paris, James R. Curran

Institutions: The University of Sydney, Commonwealth Scientific and Industrial Research Organisation, Digital Health Cooperative Research Centre, Data61

Language: English

Topic: Topic Modeling

Subfield: Artificial Intelligence

Field: Computer Science

Domain: Physical Sciences

Open Access status: hybrid

OpenAlex ID: W2948092006

FWCI: 3.539

Cites: 25

Cited by: 64

Related to: 10