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