Finite-state phrase parsing by rule sequences

We present a novel approach to parsing phrase grammars based on Eric Brill's notion of rule sequences. The basic framework we describe has somewhat less power than a finite-state machine, and yet achieves high accuracy on standard phrase parsing tasks. The rule language is simple, which makes it easy to write rules. Further, this simplicity enables the automatic acquisition of phraseparsing rules through an error-reduction strategy. This paper explores an approach to syntactic analysis that is unconventional in several respects. To begin with, we are concerned not so much with the traditional goal of analyzing the comprehensive structure of complete sentences, as much as with assigning partial structure to parts of sentences. The fragment of interest here is demonstrably a subset of the regular sets, and while these languages are traditionally analyzed with finite-state automata, our approach relies instead on the rule sequence architecture defined by Eric Brill. Why restrict ourselves to the finite-state case? Some linguistic phenomena are easier to model with regular sets than context-free grammars. Proper names are a case in point, since their syntactic distribution partially overlaps that of noun phra~ses in general; as this overlap is only partial, name analysis within a full context-free grammar is cumbersome, and some approaches have taken to include finite-state name parsers as a front-end to a principal context-free parsing stage (Jacobs et al. I99i). Proper names are of further interest, since their identifi cation is independently motivated as valuable to both information retrieval and extraction (Sundheim ~996). Further, several promising recent approaches to information extraction rely on little more than finitestate machines to perform the entire extraction analysis (Appelt et al. I993 , Grishman I995). Why approach this problem with rule sequences? In this paper we maka the case that rule sequences succeed at this task through their simplicity and speed. Most important, they support mixed-mode acquisition: the rules are both easy for an engineer to write and easy to learn automatically.