Hybrid semi-Markov CRF for Neural Sequence Labeling

ACL 2018 Zhixiu YeZhen-Hua Ling

This paper proposes hybrid semi-Markov conditional random fields (SCRFs) for neural sequence labeling in natural language processing. Based on conventional conditional random fields (CRFs), SCRFs have been designed for the tasks of assigning labels to segments by extracting features from and describing transitions between segments instead of words... (read more)

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TASK DATASET MODEL METRIC NAME METRIC VALUE GLOBAL RANK LEADERBOARD
Named Entity Recognition CoNLL 2003 (English) HSCRF F1 91.38 # 29