Summary of the paper
| Title | Semantic Feature Engineering for Enhancing Disambiguation Performance in Deep Linguistic Processing |
|---|---|
| Authors | Danielle Ben-Gera, Yi Zhang and Valia Kordoni |
| Abstract | The task of parse disambiguation has gained in importance over the last decadeas the complexity of grammars used in deep linguistic processing has beenincreasing. In this paper we propose to employ the fine-grained HPSG formalismin order to investigate the contribution of deeper linguistic knowledge to thetask of ranking the different trees the parser outputs. In particular, we focuson the incorporation of semantic features in the disambiguation component andthe stability of our model cross domains. Our work is carried out withinDELPH-IN (http://www.delph-in.net), using the LinGo Redwoods and the WeSciencecorpora, parsed with the English Resource Grammar and the PET parser. |
| Language | Semantics |
| Topics | Parsing, Grammar and Syntax, Semantics |
Full paper  |
Semantic Feature Engineering for Enhancing Disambiguation Performance in Deep Linguistic Processing |
| Bibtex | @InProceedings{BENGERA10.494, author = {Danielle Ben-Gera, Yi Zhang and Valia Kordoni}, title = {Semantic Feature Engineering for Enhancing Disambiguation Performance in Deep Linguistic Processing}, booktitle = {Proceedings of the Seventh conference on International Language Resources and Evaluation (LREC'10)}, year = {2010}, month = {may}, date = {19-21}, address = {Valletta, Malta}, editor = {Nicoletta Calzolari (Conference Chair), Khalid Choukri, Bente Maegaard, Joseph Mariani, Jan Odjik, Stelios Piperidis, Mike Rosner, Daniel Tapias}, publisher = {European Language Resources Association (ELRA)}, isbn = {2-9517408-6-7}, language = {english} } |