Foundations of statistical natural language processing
Foundations of statistical natural language processing
Building a large annotated corpus of English: the penn treebank
Computational Linguistics - Special issue on using large corpora: II
A maximum-entropy-inspired parser
NAACL 2000 Proceedings of the 1st North American chapter of the Association for Computational Linguistics conference
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
COLING '00 Proceedings of the 18th conference on Computational linguistics - Volume 2
Dependency syntax analysis using grammar induction and a lexical categories precedence system
CICLing'11 Proceedings of the 12th international conference on Computational linguistics and intelligent text processing - Volume Part I
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We present a study on the effect of adding morphological tags to the training corpus of a grammar inductor. For this purpose, we carried out several experiments using the grammar induction system called Alignment-Based Learning (ABL) and the CAST-3LB syntactically tagged Spanish corpus for training and testing. ABL produces a set of possible constituents with a word alignment process. We developed an algorithm which converts the hypotheses generated by ABL into ordered production rules. Then our algorithm groups them into possible phrase groups (constituents). These phrase groups correspond to the syntactic tagging of the unannotated text. We compared the phrase groups obtained by our algorithm with the manually tagged groups of CAST- 3LB. The experiments in the grammar induction process consisted on trying three different variants for the training corpus: (1) using words; (2) using only the morphological tags; and (3) adding morphological tags to words. Our experiments show that the inclusion of morphological tags in the grammar induction process improves significantly the performance of ABL.