JOURNAL OF SHANDONG UNIVERSITY(NATURAL SCIENCE) ›› 2015, Vol. 50 ›› Issue (11): 74-80.doi: 10.6040/j.issn.1671-9352.3.2014.095

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Temporal recognition for topic event based on shallow semantic parsing

LI Feng-huan, ZHENG De-quan, ZHAO Tie-jun   

  1. School of Computer Science and Technology, Harbin Institute of Technology, Harbin 150001, Heilongjiang, China
  • Received:2015-03-03 Revised:2015-04-21 Online:2015-11-20 Published:2015-12-09

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Abstract: Temporal recognition is a key subject in natural language processing community. The topic-related temporal information reflects the topic feature of topic events on temporal dimensionality. Most temporal recognition for events was sentence-oriented or phrase-oriented and employed static time-value machine. A temporal recogtion model for topic events was proposed in this paper. Temporal expressions were normalized with reference time dynamic-choosing mechanism in this model. Combining event extraction and shallow semantic parsing, semantic roles were mapped to temporal expressions. Document-oriented temporal recognition was implemented using sentence-oriented or phrase-oriented temporal recognition, consequently, temporal recognition for topic event segments was realized. Results show that performances of temporal recognition for topic event segments are improved by 9.6%.

Key words: topic event, event extraction, shallow semantic parsing, dynamic, temporal recognition

CLC Number: 

  • TP391
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