Abstract
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.
Work done under support of the Mexican Government (CONACYT, SNI, PIFI, and SIP-IPN).
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Juárez Gambino, O., Calvo, H. (2007). On the Usage of Morphological Tags for Grammar Induction. In: Gelbukh, A., Kuri Morales, Á.F. (eds) MICAI 2007: Advances in Artificial Intelligence. MICAI 2007. Lecture Notes in Computer Science(), vol 4827. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-540-76631-5_87
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DOI: https://doi.org/10.1007/978-3-540-76631-5_87
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