A Uniform Method of Grammar Extraction and Its Applications

A Uniform Method of Grammar Extraction and Its Applications Fei Xia and Martha Palmer and Aravind Joshi Department of Computer and Information Science University of Pennsylvania Philadelphia PA 19104, USA {fxia, mpalmer, j oshi)@linc, cis. upenn, edu Abstract Grammars are core elements of many NLP ap- plications. In this paper, we present a system that automatically extracts lexicalized gram- mars from annotated corpora. The data pro- duced by this system have been used in sev- eral tasks, such as training NLP tools (such as Supertaggers) and estimating the coverage of harid-crafted grammars. We report experi- mental results on two of those tasks and com- pare our approaches with related work. 1 Introduction There are various grammar frameworks pro- posed for natural languages. We take Lexi- calized Tree-adjoining Grammars (LTAGs) as representative of a class of lexicalized gram- mars. LTAGs (Joshi et al., 1975) are ap- pealing for representing various phenomena in natural languages due to its linguistic and computational properties. In the last decade, LTAG has been used in several aspects of natural language understanding (e.g., pars- ing (Schabes, 1990; Srinivas, 1997), semantics (Joshi and Vijay-Shanker, 1999; Kallmeyer and Joshi, 1999), and discourse (Webber and Joshi, 1998)) and a number of NLP applica- tions (e.g., machine translation (Palmer et al., 1998), information retrieval (Chandrasekar and Srinivas, 1997), and generation (Stone and Doran, 1997; McCoy et al., 1992). This paper describes a system that extracts LTAGs from annotated corpora (i.e., Treebanks). There has been much work done on extract- ing Context-Free grammars (CFGs) (Shirai et al., 1995; Charniak, 1996; Krotov et al., 1998). However, extracting LTAGs is more complicated than extracting CFGs because of the differences between LTAGs and CFGs. First, the primitive elements of an LTAG are lexicalized tree structures (called elementary trees), not context-free rules (which can be seen. as trees with depth one). Therefore, an LTAG extraction algorithm needs to examine a larger portion of a phrase structure to build an elementary tree. Second, the composition operations in LTAG are substitution (same as the one in a CFG) and adjunction. It is the operation of adjunction that distinguishes LTAG from all other formalisms. Third, un- like in CFGs, the parse trees (also known as derived trees in the LTAG) and the derivation trees (which describe how elementary trees are combined to form parse trees) are differ- ent in the LTAG formalism in the sense that a parse tree can be produced by several dis- tinct derivation trees. Therefore, to provide training data for statistical LTAG parsers, an LTAG extraction algorithm should also build derivation trees. For each phrase structure in a Treebank, our system creates a fully bracketed phrase structure, a set of elementary trees and a derivation tree. The data produced by our system have been used in several NLP tasks. We report experimental results on two of those applications and compare our ap- proaches with related work. 2 LTAG formalism The primitive elements of an LTAG are ele- mentary trees (etrees). Each etree is associ- ated …

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