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Computational Linguistics - Special issue on using large corpora: II
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Three generative, lexicalised models for statistical parsing
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Probabilistic parsing for German using sister-head dependencies
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ACL '03 Proceedings of the 41st Annual Meeting on Association for Computational Linguistics - Volume 1
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ACL '03 Proceedings of the 41st Annual Meeting on Association for Computational Linguistics - Volume 1
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CLPW '00 Proceedings of the second workshop on Chinese language processing: held in conjunction with the 38th Annual Meeting of the Association for Computational Linguistics - Volume 12
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HLT '02 Proceedings of the second international conference on Human Language Technology Research
A dependency-based method for evaluating broad-coverage parsers
IJCAI'95 Proceedings of the 14th international joint conference on Artificial intelligence - Volume 2
Morphology and reranking for the statistical parsing of Spanish
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Interactive natural language interface
WSEAS Transactions on Computers
Generic interactive natural language interface to databases (GINLIDB)
EC'09 Proceedings of the 10th WSEAS international conference on evolutionary computing
CoNLL-X shared task on multilingual dependency parsing
CoNLL-X '06 Proceedings of the Tenth Conference on Computational Natural Language Learning
Sparse multi-scale grammars for discriminative latent variable parsing
EMNLP '08 Proceedings of the Conference on Empirical Methods in Natural Language Processing
(Meta-) evaluation of machine translation
StatMT '07 Proceedings of the Second Workshop on Statistical Machine Translation
Further meta-evaluation of machine translation
StatMT '08 Proceedings of the Third Workshop on Statistical Machine Translation
Cross parser evaluation and tagset variation: a French treebank study
IWPT '09 Proceedings of the 11th International Conference on Parsing Technologies
On statistical parsing of French with supervised and semi-supervised strategies
CLAGI '09 Proceedings of the EACL 2009 Workshop on Computational Linguistic Aspects of Grammatical Inference
Statistical parsing of morphologically rich languages (SPMRL): what, how and whither
SPMRL '10 Proceedings of the NAACL HLT 2010 First Workshop on Statistical Parsing of Morphologically-Rich Languages
Handling unknown words in statistical latent-variable parsing models for Arabic, English and French
SPMRL '10 Proceedings of the NAACL HLT 2010 First Workshop on Statistical Parsing of Morphologically-Rich Languages
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ICCPOL'06 Proceedings of the 21st international conference on Computer Processing of Oriental Languages: beyond the orient: the research challenges ahead
EMNLP '11 Proceedings of the Conference on Empirical Methods in Natural Language Processing
Adaptation of data and models for probabilistic parsing of portuguese
PROPOR'06 Proceedings of the 7th international conference on Computational Processing of the Portuguese Language
Discriminative strategies to integrate multiword expression recognition and parsing
ACL '12 Proceedings of the 50th Annual Meeting of the Association for Computational Linguistics: Long Papers - Volume 1
An information-theoretic measure to evaluate parsing difficulty across treebanks
ACM Transactions on Speech and Language Processing (TSLP)
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Parsing models for identifying multiword expressions
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ACM Transactions on Speech and Language Processing (TSLP) - Special issue on multiword expressions: From theory to practice and use, part 2
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This paper presents the first probabilistic parsing results for French, using the recently released French Treebank. We start with an unlexicalized PCFG as a baseline model, which is enriched to the level of Collins' Model 2 by adding lexicalization and subcategorization. The lexicalized sister-head model and a bigram model are also tested, to deal with the flatness of the French Treebank. The bigram model achieves the best performance: 81% constituency F-score and 84% dependency accuracy. All lexicalized models outperform the unlexicalized baseline, consistent with probabilistic parsing results for English, but contrary to results for German, where lexicalization has only a limited effect on parsing performance.