Robust stochastic parsing: comparing two approaches for processing extra-grammatical sentences
| Authors | |
|---|---|
| Year of publication | 2005 |
| Type | Article in Proceedings |
| Conference | Proceedings of the 15th Nordic Conference of Computational Linguistics (NODALIDA) 2005 |
| MU Faculty or unit | |
| Citation | |
| Field | Informatics |
| Keywords | robust; parsing; NLP |
| Description | This paper compares two techniques for robust parsing of extra-grammatical natural language that might be of interest in large scale Textual Data Analysis applications. The first one returns a "correct" derivation for any extra-grammatical sentence by generating the finest corresponding most probable optimal maximum coverage. The second one extends the initial grammar by adding relaxed grammar rules in a controlled manner. Both techniques use a stochastic parser that selects a "best" solution among multiple analyses. The techniques were tested on the ATIS and Susanne corp ora and exp erimental results, as well as conclusions on performance comparison, are provided. |
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