A parallel parsing system for natural language analysis
Proceedings on Third international conference on logic programming
Linguistic knowledge acquisition from parsing failures
EACL '93 Proceedings of the sixth conference on European chapter of the Association for Computational Linguistics
Automatic acquisition of subcategorization frames from untagged text
ACL '91 Proceedings of the 29th annual meeting on Association for Computational Linguistics
Automatic acquisition of a large subcategorization dictionary from corpora
ACL '93 Proceedings of the 31st annual meeting on Association for Computational Linguistics
Some chart-based techniques for parsing ill-formed input
ACL '89 Proceedings of the 27th annual meeting on Association for Computational Linguistics
Chart parsing of robust grammars
COLING '92 Proceedings of the 14th conference on Computational linguistics - Volume 1
COLING '92 Proceedings of the 14th conference on Computational linguistics - Volume 2
Combination of symbolic and statistical approaches for grammatical knowledge acquisition
ANLC '94 Proceedings of the fourth conference on Applied natural language processing
| Hi-index | 0.00 |
This paper presents some techniques for selecting linguistically adequate hypotheses of new grammatical knowledge to be used as resources of grammatical knowledge acquisition. In our framework of linguistic knowledge acquisition, a rule-based hypothesis generator is invoked in case of parsing failures and all the possible hypotheses of new grammar rules or lexical entries are generated from partial parsing results. Although each hypothesis could recover the defects of the existing grammar, the greater part of hypotheses are linguistically unnatural. The techniques we propose here prevent such unnatural hypotheses from being generated without discarding plausible ones and make the following corpus-based acquisition process more efficient and more reliable.