This page describes ongoing work to incorporate more lexical semantics into DELPH-IN.

Prelimary work is being done using the ERG and wordnet, mainly at NTU (FrancisBond, MathieuMorey) and UW (ZinaPozen).

Content

To Maybe Do

  • learn first senses from a large corpus in the style of McCarthy et al (2004) and use these to train the generative model — especially useful for non-English

References

  • Sanae Fujita, Francis Bond, Stephan Oepen, and Takaaki Tanaka (2007) Exploiting semantic information for HPSG parse selection. In ACL 2007 Workshop on Deep Linguistic Processing, pages 25–32, Prague. (.bib)
  • Stephan Oepen, Erik Velldal, Jan Tore Lønning, Paul Meurer, Victoria Rosén, and Dan Flickinger. Towards hybrid quality-oriented machine translation. On linguistics and probabilities in MT. In Proceedings of the 10th International Conference on Theoretical and Methodological Issues in Machine Translation, Skövde, Sweden, 2007.
  • E. Velldal. Empirical Realization Ranking Ph.D. thesis, Department of Informatics, University of Oslo Oslo, Norway, 2008
  • Sanae Fujita, Francis Bond, Takaaki Tanaka and Stephan Oepen (2010). Exploiting Semantic Information for HPSG Parse Selection. Research on Language and Computation, 8(1), 1–22.

Last update: 2013-07-29 by FrancisBond [edit]