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Analyzing holistic parsers: implications for robust parsing and systematicity
1Department of Computing, Hong Kong Polytechnic University, Hung Hom, Kowloon, Hong Kong.
Neural Computation
|May 22, 2001
Summary
Holistic parsers, like the confluent preorder parser (CPP), offer robust parsing by directly mapping sentence to parse tree representations. This study reveals how CPP corrects grammatical errors and emphasizes the importance of distributed representations for generalization.
Area of Science:
- Computational Linguistics
- Natural Language Processing
- Artificial Intelligence
Background:
- Holistic parsers provide an alternative to traditional algorithmic parsers, demonstrating inherent robustness and good generalization.
- Their mechanism involves direct mapping from connectionist sentence representations to parse tree representations, requiring minimal prior knowledge.
- Understanding the internal operations of holistic parsers, particularly the confluent preorder parser (CPP), remains a challenge.
Purpose of the Study:
- To analyze the operational mechanisms of the confluent preorder parser (CPP) by viewing it as a dynamical system.
- To elucidate the step-by-step inference process underlying holistic parsing and understand error correction.
- To investigate the role of parse tree representation distribution in generalization performance.
Main Methods:
- The confluent preorder parser (CPP) was analyzed as a dynamical system, with parsing viewed as state transitions.
- The study tracked state transitions during parsing to understand intermediate decisions and error correction.
- Representational space distribution of linearized parse trees was examined in relation to generalization.
Main Results:
- Grammatical errors cause deviations in the CPP's parsing trajectory, which then converges to the correct parse tree.
- The study demonstrates that systematic parse tree representations alone are insufficient for good generalization.
- Distributed representations in specific locations of the representational space are crucial for generalization, with preorder traversal encoding proving effective.
Conclusions:
- Holistic parsing, exemplified by the CPP, can be understood as a sequential inference process through state transitions.
- The CPP effectively corrects grammatical errors by guiding parsing trajectories back to the correct structure.
- Effective generalization in holistic parsing relies on the distributed nature and strategic placement of parse tree representations, not just their systematic encoding.