The Use of Syntactic Clues in Discourse Processing

THE USE OF SYNTACTIC CLUES IN DISCOURSE PROCESSING Nan Decker 1834 Chase Avenue Cincinnati, Ohio 45223, USA ABSTRACT The desirability of a syntactic parsing com- ponent in natural language understanding systems has been the subject of debate for the past several years. This paper describes an approach to auto- marie text processing which is entirely based on syntactic form. A program is described which processes one genre of discourse, that of news- paper reports. The program creates summaries of reports by relying on an expanded concept of text grounding: certain syntactic structures and tense/ aspect oairs indicate the most important events in a news story. Supportive, background material is also highly coded syntactically. Certain types of information are routinely expressed with distinct syntactic forms. Where more than one episode occurs in a single report, a change of episode will also be marked syntactically in a reliable way. INTRODUCTION The role that syntactic structure should play in natural language processing has been a matter of debate in computational linguistics. While some researchers eschew syntactic processing as giving a poor return on the heavy investment of a parser (Schank and Riesbeck, 1981), others make syntactic representations the basis from which further work is done (Sager, 1981; Hirschman and Sager, 1982). Current syntax-based processors tend to work only within a narrow semantic domain, since they rely heavily on word co-occurrence patterns which hold only within texts from a part° icular sublangua&e. Knowledge-based processors, on the other hand, can operate on a less restricted semantic field, but only if sufficient knowledge in the form of scripts, frames, and so forth, is built into the program. This paper describes a syntactic approach to natural language processing which is not bound to a narrow semantic field, and which requires little or no world knowledge. This approach has been demonstrated in a computer program called DUMP (~iscourse Understanding model [rogram), which relies solely on syntactic structure to create summaries of one particular genre of discourse-- that of newspaper reports--and to label the kinds of information given in them (Decker, 1985). The process for creating these summaries differs sub- stantially from the word-llst and statistical methods used by other automatic abstractor programs (Borko and Beruier, 1975). The DUMP program therefore depends on a predictable discourse genre or style, rather than a predictable sublang- uage lexicon or body of world knowledge. DUMP was developed from a corpus of over 5800 words representing twenty-three news reports from three daily newspapers: the New York Times, the Boston Globe, and the Providence Journal/Evenin~ Bulletin. With one exception, each story appeared in the upper right-hand column of the front page. The stories in the corpus were chosen randomly and the only criterion for rejection was too large a percentage of quoted material. Only the first two hundred words or so of each story were included in the corpus in order to allow a greater samplin~ of reports. The discourse principles at work are fairly represented in an excerpt o ~ this length. The …

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