The ups and downs of lexical acquisition
AAAI '94 Proceedings of the twelfth national conference on Artificial intelligence (vol. 1)
Learning from texts - a terminological metareasoning perspective
Connectionist, Statistical, and Symbolic Approaches to Learning for Natural Language Processing
Automatic acquisition of subcategorization frames from untagged text
ACL '91 Proceedings of the 29th annual meeting on Association for Computational Linguistics
Incremental identification of inflectional types
COLING '00 Proceedings of the 18th conference on Computational linguistics - Volume 1
Lexicon acquisition with a large-coverage unification-based grammar
EACL '03 Proceedings of the tenth conference on European chapter of the Association for Computational Linguistics - Volume 2
Processing unknown words in a dialogue system
SIGDIAL '02 Proceedings of the 3rd SIGdial workshop on Discourse and dialogue - Volume 2
Computer aided correction and extension of a syntactic wide-coverage lexicon
COLING '08 Proceedings of the 22nd International Conference on Computational Linguistics - Volume 1
The corpus and the lexicon: standardising deep lexical acquisition evaluation
DeepLP '07 Proceedings of the Workshop on Deep Linguistic Processing
Acquisition of unknown word paradigms for large-scale grammars
COLING '10 Proceedings of the 23rd International Conference on Computational Linguistics: Posters
| Hi-index | 0.00 |
The lexical acquisition system presented in this paper incrementally updates linguistic properties of unknown words inferred from their surrounding context by parsing sentences with an HPSG grammar for German. We employ a gradual, information-based concept of "unknownness" providing a uniform treatment for the range of completely known to maximally unknown lexical entries. "Unknown" information is viewed as revisable information, which is either generalizable or specializable. Updating takes place after parsing, which only requires a modified lexical lookup. Revisable pieces of information are identified by grammar-specified declarations which provide access paths into the parse feature structure. The updating mechanism revises the corresponding places in the lexical feature structures iff the context actually provides new information. For revising generalizable information, type union is required. A worked-out example demonstrates the inferential capacity of our implemented system.