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The Exploration of Deterministic and Efficient Dependency Parsing

The Exploration of Deterministic and Efficient Dependency Parsing. National Central University , Taiwan Ming Chuan University , Taiwan. Yu-Chieh Wu Yue-Shi Lee Jie-Chi Yang. Date: 2006/6/8 Reporter: Yu-Chieh Wu. Context. Nivre ’ s method is a LINEAR-TIME parsing algorithm

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The Exploration of Deterministic and Efficient Dependency Parsing

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  1. The Exploration of Deterministic and Efficient Dependency Parsing National Central University, Taiwan Ming Chuan University, Taiwan Yu-Chieh Wu Yue-Shi Lee Jie-Chi Yang Date: 2006/6/8 Reporter: Yu-Chieh Wu

  2. Context • Nivre’s method is a LINEAR-TIME parsing algorithm • But it presumed the projective grammar relation for text • One solution is to applying the psuedo projectivization (Nivre and Nilson, 2005) • In addition, non-projective words or roots were still kept in stack • Un-parsed words • In multilingual scenario, some languages annotated labels for roots

  3. In this paper • Extend the time efficiency of the Nivre’s method • DO NOT scan the word sequence multiple times • Perform the Niver’s algorithm • Only focused on the “UN-PARSED” words • Efficiently label the roots

  4. Parsed Text Nivre’s Parser Root Parser Post- Processor Un-Parsed Text Learner 1 Learner 2 Learner 3 Un-Parsed Words Un-Parsed Words System Overview

  5. Our solution is… • To reduce the un-parsed rate • We performed both • Forward parsing • Backward parsing directions (usually better) • To classify the remaining words in stacks • A root parser to identify the word is… • Root (including root label) or not root • To re-connect the non-projective words • A post-processor is used to re-construct the arcs • Exhaustive from the sentence start • Regardless its children

  6. Statistics of un-parsed rate (percentage)

  7. Wordi+1 Child0 Wordi-2 Wordi-1 Wordi ChildR Wordi+2 Bigrami+2 Bigrami+1 Bigrami Bigram Bigrami-1 Bigrami-2 Bigram BiPOS BiPOSi+2 BiPOS BiPOSi BiPOSi-1 BiPOSi-2 BiPOSi+1 Root Parser For each un-parsed words

  8. Experimental Results

  9. Parsing performance of different grained POS tags and forward/backward parsing directions

  10. Conclusion • In this paper, we investigate the how effect does the “fast parser” achieve • The employed features were quite simple • Only C/F-POS tag and word form • We extend the Nivre’s method • Root parser • Exhaustive post-processing

  11. Questions ?

  12. System Spec

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