🤔 Joint Detection and Coreference Resolution of Entities and Events with Document-level Context Aggregation (ACL21 SRW)

[hideaki-j]

Joint Detection and Coreference Resolution of Entities and Events with Document-level Context Aggregation

Contribution summary

• Kriman et al. proposed IE (including entity CR) model which handles full-document as a context,
• to understand cross-sentence dependencies, and
• achieved higher performance than baseline model, OneIE.

Authors

Samuel Kriman and Heng Ji (University of Illinois at Urbana-Champaign)

Motivation

• Existing methods focus on extracting information from sentences or paragraphs, meaning cannot consider full-document context
• To improve performance, Incorporating cross-sentence dependencies is needed

Method

• Proposed IE model that can be used for IE subtasks, including entity CR (coreference resolution), at the document level
• Input is a document and output are mention-entity and/or mention-events pairs
• Steps
  • Generate representation for the mentions, including pronouns
  • ?

Results / Insight

• Dataset: ACE05-E+, OIE dataset including pronoun mention annotations
• Entity and event trigger extraction results
  • Higher than baseline model of OneIE
• Coref results
  • F1 B³_sys: 84.83
  • No baseline is set

Questions

• How do the representations are used to identify corresponding entities and events?

[hideaki-j]

Others

• Code: https://github.com/sam1373/long_ie