Entity-Relation Extraction as Multi-Turn Question Answering

ACL 2019 Xiaoya LiFan YinZijun SunXiayu LiArianna YuanDuo ChaiMingxin ZhouJiwei Li

In this paper, we propose a new paradigm for the task of entity-relation extraction. We cast the task as a multi-turn question answering problem, i.e., the extraction of entities and relations is transformed to the task of identifying answer spans from the context... (read more)

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Results from the Paper


TASK DATASET MODEL METRIC NAME METRIC VALUE GLOBAL RANK RESULT LEADERBOARD
Relation Extraction ACE 2004 Multi-turn QA Entity+Relation F1 49.4 # 2
Entity F1 83.6 # 2
Relation Extraction ACE 2005 Multi-turn QA Relation F1 60.2 # 3
Entity F1 84.8 # 3
Relation Extraction CoNLL04 Multi-turn QA Entity F1 87.8 # 2
Relation F1 68.9 # 1
Relation F1 68.9 # 2

Methods used in the Paper


METHOD TYPE
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