| Title | Semi-automatic Syntactic and Semantic Corpus Annotation with a Deep Parser |
| Author(s) |
Mary D. Swift, Myroslava 0. Dzikovska, Joel R. Tetreault, James F. Allen
Department of Computer Science, University of Rochester |
| Session | P18-S |
| Abstract | We describe a semi-automatic method for linguistically rich corpus annotation using a broad-coverage deep parser to generate syntactic structure, semantic representation and discourse information for task-oriented dialogs. The parser-generated analyses are checked by trained annotators. Incomplete coverage and incorrect analyses are addressed through lexicon and grammar development, after which the dialogs undergo another cycle of parsing and checking. Currently we have 85% correct annotations in our emergency rescue task domain and 70% in our medication scheduling domain. This iterative process of corpus annotation allows us to create domain-specific gold-standard corpora for test suites and corpus-based experiments as part of general system development. |
| Keyword(s) | Corpus annotation, deep parsing, syntax, semantics |
| Language(s) | English |
| Full Paper | 714.pdf |