Neural Segmental Hypergraphs for Overlapping Mention Recognition

In this work, we propose a novel segmental hypergraph representation to model overlapping entity mentions that are prevalent in many practical datasets. We show that our model built on top of such a new representation is able to capture features and interactions that cannot be captured by previous models while maintaining a low time complexity for inference... (read more)

PDF Abstract EMNLP 2018 PDF EMNLP 2018 Abstract

Results from the Paper


TASK DATASET MODEL METRIC NAME METRIC VALUE GLOBAL RANK BENCHMARK
Nested Named Entity Recognition ACE 2004 Neural segmental hypergraphs F1 75.1 # 6
Named Entity Recognition ACE 2004 Neural segmental hypergraphs F1 75.1 # 5
Nested Mention Recognition ACE 2004 Neural segmental hypergraphs F1 75.1 # 5
Nested Named Entity Recognition ACE 2005 Neural segmental hypergraphs F1 74.5 # 9
Named Entity Recognition ACE 2005 Neural segmental hypergraphs F1 74.5 # 9
Nested Mention Recognition ACE 2005 Neural segmental hypergraphs F1 74.5 # 7
Named Entity Recognition GENIA Neural segmental hypergraphs F1 75.1 # 6
Nested Named Entity Recognition GENIA Neural segmental hypergraphs F1 75.1 # 9

Methods used in the Paper


METHOD TYPE
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