Inducing Temporal Graphs

We consider the problem of constructing a directed acyclic graph that encodes temporal relations found in a text. The unit of our analysis is a temporal segment, a fragment of text that maintains temporal coherence. The strength of our approach lies in its ability to simultaneously optimize pairwise ordering preferences and global constraints on the graph topology. Our learning method achieves 83% F-measure in temporal segmentation and 84% accuracy in inferring temporal relations between two segments.

• Publication year

  2006

• Venue

  Conference on Empirical Methods in Natural Language Processing

• Publication date

  2006-07-22

• Fields of study

  Computer Science

• Identifiers
  DOI 10.3115/1610075.1610105
• External record

  Open on Semantic Scholar

• Source metadata

  Semantic Scholar

• No claims are published for this paper.

• No concepts are published for this paper.

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