Syntactic Analysis of Natural Language Using Linguistic Rules and Corpus-Based Patterns

SYNTACTIC ANALYSIS OF NATURAL LANGUAGE USING LINGUISTIC RULES AND CORPUS-BASED PATTER.NS Pasi Tapanainen* Timo J~rvinen Rank Xerox Research Centre Grenoble Laboratory University of tIelsinki Research Unit for Computational Linguistics Abstract We are concerned with the syntactic annotation of unrestricted text. We combine a rule-based analysis with subsequent exploitation of empiri- cal data. The rule~based surface syntactic anal- yser leaves some amount of ambiguity in the out- put that is resolved using empirical patterns. We have implemented a system for generating and applying corpus-based patterns. Somc patterns describe the main constituents in the sentence and some the local context of the each syntac- tic function. There are several (partly) redml- tant patterns, and the "pattern" parser selects analysis of the sentence ttmt matches the strictest possible pattern(s). The system is applied to an experimeutal corpus. We present the results and discuss possible refinements of the method from a linguistic point of view. 1 INTRODUCTION We discuss surface-syntactic analysis of running text. Our purpose is to mark each word with a syntactic tag. The tags denote subjects, object, main verbs, adverbials, etc. They are listed in Appendix A. Our method is roughly following • Assign to each word all the possible syntactic tags. • Disambiguate words as much as possible using lin- guistic information (hand-coded rules). Ilere we avoid risks; we rather leave words ambiguous than guess wrong. • Use global patterns to form alternative sentence level readings. Those alternatiw~" analyses are se- lected that match the strictest global pattern. [f it does not accept any of the remaining readings, the second strictest pattern is used, and so on. • Use local patterns to rank the remaining readings. The local patterns contain possible contexts for syn- tactic functions. The ranking of the readings de- pends on the length of the contexts associated with the syntactic functions of the sentece. We use both linguistic knowledge, represented as rules, and empirical data collected from tagged cor- pora. We describe a new way to collect information from a tagged corpus and a way to apply it. In this paper, we are mainly concerned with exploiting the empirical data and combining two different kinds of parsers. *This work was done when the author worked in the Research Unit for Computational Linguistics at the Uni- versity of Itelsinki. Our work is based on work done with ENGCG, the Constraint Grammar Parser of English [Karls- son, 1990; Karlsson, 1994; Karlsson et al., 1994; Voutilainen, 1994]. It is a rule-h~ed tagger and surface-syntactic parser that makes a very small num- her of errors but leaves some words ambiguous i.e. it prefers ambiguity to guessing wrong. The morpholog- ical part-of-speech analyser leaves [Voutilainen et al., 1992] only 0.3 % of all words in running text without the correct analysis when 3-6 % of words still have two or Inore I analyses. Vontilainen, Ileikkil'5. and Anttila [1992] reported that the syntactic analyser leaves :3-3.5 % of words without the correct syntactic tag, and 15-20 % of words remain amhiguos. Currently, the …

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