1 / 10

Multiword expressions extraction

Multiword expressions extraction. Hung_H3. Multiword Expressions (MWEs). MWEs MWE Extraction Pavel’s work Various tests on MWE’s properties. Properties of MWEs. MWEs: Multiple simplex words Idiosyncratic Lexically: ad hoc Syntactically: by and large (  prep conj adj?)

keelty
Download Presentation

Multiword expressions extraction

An Image/Link below is provided (as is) to download presentation Download Policy: Content on the Website is provided to you AS IS for your information and personal use and may not be sold / licensed / shared on other websites without getting consent from its author. Content is provided to you AS IS for your information and personal use only. Download presentation by click this link. While downloading, if for some reason you are not able to download a presentation, the publisher may have deleted the file from their server. During download, if you can't get a presentation, the file might be deleted by the publisher.

E N D

Presentation Transcript

  1. Multiword expressions extraction Hung_H3

  2. Multiword Expressions (MWEs) • MWEs • MWE Extraction • Pavel’s work • Various tests on MWE’s properties

  3. Properties of MWEs • MWEs: • Multiple simplex words • Idiosyncratic • Lexically: ad hoc • Syntactically: by and large ( prep conj adj?) • Semantically: spill the beans • Statistically: good morning • Obstacles to language understanding, translation, generation, etc.

  4. MWEs Extraction • MWEs Extraction • Formularize MWEs’ identifying properties • Association measures • Association measures of MWEs • Statistically marked  co-occurrence’s measures • Semantically non-compositional  compositionality’s measures • ?

  5. Pavel (2005, 2006, 2008)Combination of 82 association measures • Statistical tests: • Mutual information • Statistical independence • Likely-hood measures • Semantics tests: • Entropy of immediate context • Immediate context: immediately preceding/following words • Diversity of empirical context • Empirical context: words within a certain specified window

  6. Pavel (2005, 2006, 2008)Combination of 82 association measures • Result: • MAP: 80.81% • “Equivalent” measures  17 measures • Issues: • Possible conflicting predictions • All combined is best? • Unclear linguistic and/or statistical significance

  7. Other linguistics-driven tests • MWEs are lexically fixed? • Substitutability test (Lin, 1999) • MWEs are order-specific? • Permutation entropy (PE) (Yi Zhang et al., 2006) • Entropy of Permutation and Insertion (EPI) • (Aline et al., 2008) • Not all permutations are valid • “Permutation”  “Syntactic variants” • Others…?

  8. References • T. Baldwin. 2004. Multiword Expressions tutorial. • D. Lin. 1999. Automatic identification of non-compositional phrases. In ACL 1999. • Pavel Pecina and Pavel Schlesinger. 2006. Combining association measures for collocation extraction. In ACL 2006. • P. Pecina. 2008. A machine learning approach to Multiword Expression extraction. In MWE Shared task 2008. • A. Villavicencio et al. 2008. An Evaluation of Methods for the Extraction of Multiword Expressions. In MWE Shared task 2008. • Yi Zhang et al. 2006 Automated multiword expression prediction for grammar engineering. In ACL 2006. • Wikipedia: http://www.wikipedia.org/

  9. Hung_H3 Thank You !

  10. References

More Related