Summary of the paper
| Title | A Database of Narrative Schemas |
|---|---|
| Authors | Nathanael Chambers and Dan Jurafsky |
| Abstract | This paper describes a new language resource of events and semantic roles that characterize real-world situations. Narrative schemas contain sets of related events (edit and publish), a temporal ordering of the events (edit before publish), and the semantic roles of the participants (authors publish books). This type of world knowledge was central to early research in natural language understanding, scripts being one of the main formalisms, they represented common sequences of events that occur in the world. Unfortunately, most of this knowledge was hand-coded and time consuming to create. Current machine learning techniques, as well as a new approach to learning through coreference chains, has allowed us to automatically extract rich event structure from open domain text in the form of narrative schemas. The narrative schema resource described in this paper contains approximately 5000 unique events combined into schemas of varying sizes. We describe the resource, how it is learned, and a new evaluation of the coverage of these schemas over unseen documents. |
| Topics | Knowledge Discovery/Representation, Statistical and machine learning methods, Semantics |
Full paper |
A Database of Narrative Schemas |
Slides |
A Database of Narrative Schemas |
| Bibtex | @InProceedings{CHAMBERS10.58, author = {Nathanael Chambers and Dan Jurafsky}, title = {A Database of Narrative Schemas}, 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} } |