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An Unsupervised Approach for Linking Automatically Extracted and Manually Crafted LTAGs

  • Conference paper
Computational Linguistics and Intelligent Text Processing (CICLing 2011)

Part of the book series: Lecture Notes in Computer Science ((LNTCS,volume 6608))

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Abstract

Though the lack of semantic representation of automatically extracted LTAGs is an obstacle in using these formalism, due to the advent of some powerful statistical parsers that were trained on them, these grammars have been taken into consideration more than before. Against of this grammatical class, there are some widely usage manually crafted LTAGs that are enriched with semantic representation but suffer from the lack of efficient parsers. The available representation of latter grammars beside the statistical capabilities of former encouraged us in constructing a link between them.

Here, by focusing on the automatically extracted LTAG used by MICA [4] and the manually crafted English LTAG namely XTAG grammar [32], a statistical approach based on HMM is proposed that maps each sequence of former elementary trees onto a sequence of later elementary trees. To avoid of converging the HMM training algorithm in a local optimum state, an EM-based learning process for initializing the HMM parameters were proposed too. Experimental results show that the mapping method can provide a satisfactory way to cover the deficiencies arises in one grammar by the available capabilities of the other.

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Author information

Authors and Affiliations

  1. Department of ECE, University of Tehran, Tehran, Iran

    Heshaam Faili

  2. Department of Computer Engineering, Islamic Azad University, Science and Research, Tehran, Iran

    Ali Basirat

Authors
  1. Heshaam Faili
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  2. Ali Basirat
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Editor information

Editors and Affiliations

  1. Center for Computing Research, National Polytechnic Institute, Mexico

    Alexander F. Gelbukh

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Faili, H., Basirat, A. (2011). An Unsupervised Approach for Linking Automatically Extracted and Manually Crafted LTAGs. In: Gelbukh, A.F. (eds) Computational Linguistics and Intelligent Text Processing. CICLing 2011. Lecture Notes in Computer Science, vol 6608. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-19400-9_6

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  • DOI: https://doi.org/10.1007/978-3-642-19400-9_6

  • Publisher Name: Springer, Berlin, Heidelberg

  • Print ISBN: 978-3-642-19399-6

  • Online ISBN: 978-3-642-19400-9

  • eBook Packages: Computer ScienceComputer Science (R0)

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