Summary of the paper
| Title | Extracting Surface Realisation Templates from Corpora |
|---|---|
| Authors | Thiago D. Tadeu, Eder M. de Novais and Ivandré Paraboni |
| Abstract | In Natural Language Generation (NLG), template-based surface realisation is an effective solution to the problem of producing surface strings from a given semantic representation, but many applications may not be able to provide the input knowledge in the required level of detail, which in turn may limit the use of the available NLG resources. However, if we know in advance what the most likely output sentences are (e.g., because a corpus on the relevant application domain happens to be available), then corpus knowledge may be used to quickly deploy a surface realisation engine for small-scale applications, for which it may be sufficient to select a sentence (in natural language) that resembles the desired output, and then modify some or all of its constituents accordingly. In other words, the application may simply 'point to' an existing sentence in the corpus and specify only the changes that need to take place to obtain the desired surface string. In this paper we describe one such approach to surface realisation, in which we extract syntactically-structured templates from a target corpus, and use these templates to produce existing and modified versions of the target sentences by a combination of canned text and basic dependency-tree operations. |
| Topics | Natural Language Generation, Tools, systems, applications, Other |
Full paper |
Extracting Surface Realisation Templates from Corpora |
Slides |
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| Bibtex | @InProceedings{TADEU10.715, author = {Thiago D. Tadeu and Eder M. de Novais and Ivandré Paraboni}, title = {Extracting Surface Realisation Templates from Corpora}, 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} } |