Using an annotated corpus as a stochastic grammar
EACL '93 Proceedings of the sixth conference on European chapter of the Association for Computational Linguistics
A state-transition grammar for data-oriented parsing
EACL '95 Proceedings of the seventh conference on European chapter of the Association for Computational Linguistics
A DOP model for semantic interpretation
ACL '98 Proceedings of the 35th Annual Meeting of the Association for Computational Linguistics and Eighth Conference of the European Chapter of the Association for Computational Linguistics
A computational model of language performance: Data Oriented Parsing
COLING '92 Proceedings of the 14th conference on Computational linguistics - Volume 3
Learning log-linear models on constraint-based grammars for disambiguation
Learning language in logic
Supertagging: an approach to almost parsing
Computational Linguistics
Natural Language Engineering
Context-sensitive spoken dialogue processing with the DOP model
Natural Language Engineering
Experiments with corpus-based LFG specialization
ANLC '00 Proceedings of the sixth conference on Applied natural language processing
An empirical evaluation of LFG-DOP
COLING '00 Proceedings of the 18th conference on Computational linguistics - Volume 1
Parsing with the shortest derivation
COLING '00 Proceedings of the 18th conference on Computational linguistics - Volume 1
COLING '02 Proceedings of the 19th international conference on Computational linguistics - Volume 1
What is the minimal set of fragments that achieves maximal parse accuracy?
ACL '01 Proceedings of the 39th Annual Meeting on Association for Computational Linguistics
An improved parser for data-oriented lexical-functional analysis
ACL '00 Proceedings of the 38th Annual Meeting on Association for Computational Linguistics
Overfitting avoidance for stochastic modeling of attribute-value grammars
ConLL '00 Proceedings of the 2nd workshop on Learning language in logic and the 4th conference on Computational natural language learning - Volume 7
Abductive explanation-based learning improves parsing accuracy and efficiency
SIGHAN '03 Proceedings of the second SIGHAN workshop on Chinese language processing - Volume 17
| Hi-index | 0.00 |
We develop a Data-Oriented Parsing (DOP) model based on the syntactic representations of Lexical-Functional Grammar (LFG). We start by summarizing the original DOP model for tree representations and then show how it can be extended with corresponding functional structures. The resulting LFG-DOP model triggers a new, corpus-based notion of grammaticality, and its probability models exhibit interesting behavior with respect to specificity and the interpretation of ill-formed strings.