The logic of typed feature structures
The logic of typed feature structures
Skeptical and credulous default unification with applications to templates and inheritance
Inheritance, defaults and the lexicon
Defaults in lexical representation
Inheritance, defaults and the lexicon
A maximum entropy approach to natural language processing
Computational Linguistics
Generalized probabilistic LR parsing of natural language (Corpora) with unification-based grammars
Computational Linguistics - Special issue on using large corpora: I
Stochastic attribute-value grammars
Computational Linguistics
Estimators for stochastic "Unification-Based" grammars
ACL '99 Proceedings of the 37th annual meeting of the Association for Computational Linguistics on Computational Linguistics
Lenient default unification for robust processing within unification based grammar formalisms
COLING '02 Proceedings of the 19th international conference on Computational linguistics - Volume 1
Dynamic programming for parsing and estimation of stochastic unification-based grammars
ACL '02 Proceedings of the 40th Annual Meeting on Association for Computational Linguistics
Parsing with generative models of predicate-argument structure
ACL '03 Proceedings of the 41st Annual Meeting on Association for Computational Linguistics - Volume 1
ACL '00 Proceedings of the 38th Annual Meeting on Association for Computational Linguistics
Learning as search optimization: approximate large margin methods for structured prediction
ICML '05 Proceedings of the 22nd international conference on Machine learning
Parsing the WSJ using CCG and log-linear models
ACL '04 Proceedings of the 42nd Annual Meeting on Association for Computational Linguistics
Probabilistic disambiguation models for wide-coverage HPSG parsing
ACL '05 Proceedings of the 43rd Annual Meeting on Association for Computational Linguistics
Coarse-to-fine n-best parsing and MaxEnt discriminative reranking
ACL '05 Proceedings of the 43rd Annual Meeting on Association for Computational Linguistics
Deterministic dependency parsing of English text
COLING '04 Proceedings of the 20th international conference on Computational Linguistics
The importance of supertagging for wide-coverage CCG parsing
COLING '04 Proceedings of the 20th international conference on Computational Linguistics
A best-first probabilistic shift-reduce parser
COLING-ACL '06 Proceedings of the COLING/ACL on Main conference poster sessions
Maximum entropy estimation for feature forests
HLT '02 Proceedings of the second international conference on Human Language Technology Research
Extremely lexicalized models for accurate and fast HPSG parsing
EMNLP '06 Proceedings of the 2006 Conference on Empirical Methods in Natural Language Processing
A log-linear model with an n-gram reference distribution for accurate HPSG parsing
IWPT '07 Proceedings of the 10th International Conference on Parsing Technologies
Efficient HPSG parsing with supertagging and CFG-filtering
IJCAI'07 Proceedings of the 20th international joint conference on Artifical intelligence
A classifier-based parser with linear run-time complexity
Parsing '05 Proceedings of the Ninth International Workshop on Parsing Technology
Optimistic backtracking: a backtracking overlay for deterministic incremental parsing
HLT-SS '11 Proceedings of the ACL 2011 Student Session
HLT '11 Proceedings of the 49th Annual Meeting of the Association for Computational Linguistics: Human Language Technologies - Volume 1
CuteForce: deep deterministic HPSG parsing
IWPT '11 Proceedings of the 12th International Conference on Parsing Technologies
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Many parsing techniques including parameter estimation assume the use of a packed parse forest for efficient and accurate parsing. However, they have several inherent problems deriving from the restriction of locality in the packed parse forest. Deterministic parsing is one of solutions that can achieve simple and fast parsing without the mechanisms of the packed parse forest by accurately choosing search paths. We propose (i) deterministic shift-reduce parsing for unification-based grammars, and (ii) best-first shift-reduce parsing with beam thresholding for unification-based grammars. Deterministic parsing cannot simply be applied to unification-based grammar parsing, which often fails because of its hard constraints. Therefore, it is developed by using default unification, which almost always succeeds in unification by overwriting inconsistent constraints in grammars.