Towards efficient probabilistic HPSG parsing: integrating semantic and syntactic preference to guide the parsing
نویسندگان
چکیده
We present a framework for efficient parsing with probabilistic Head-driven Phrase Structure Grammars (HPSG). The parser can integrate semantic and syntactic preference into figures-of-merit (FOMs) with the equivalence class function during parsing, and reduce the search space by using the integrated FOMs. This paper presents a CKY algorithm with this function and experimental results of beam thresholding. We also present an iterative CKY parsing for HPSG, which should further speed up parsing in runtime.
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