Recovering Implicit Information

This paper describes the SDC PUNDIT, (Prolog UNDerstands Integrated Text), system for processing natura l language messages. 1 PUNDIT, written in Prolog, is a highly modular system consisting of distinct syntactic, semantic and pragmatics components. Each component draws on one or more sets of data, including a lexicon, a broad-coverage grammar of EngLish, semantic verb decompositions, rules mapping between syntactic and semantic constituents, and a domain model. This paper discusses the communication between the syntactic, semantic and pragmatic modules that is necessary for making implicit linguistic information explicit. The key is letting syntax and semantics recognize missing linguistic entities as implicit entities, so that they can be labelled as such, and referenee resolution can be directed to find specific referents for the entities. In this way the task of making implicit linguistic information explicit becomes a subset of the tasks performed by reference resolution. The success of this approach is dependent on marking missing syntactic constituents as elided and missing semantic roles as ESSENTIAL so that reference resolution can know when to look for referents. 1. I n t r o d u c t i o n This paper describes the SDC PUNDIT 2 system for processing natural language messages. PUNDIT, written in Prolog, is a highly modular system consisting of distinct syntactic, semantic and pragmatics components. Each component draws on one or more sets of data, including a lexicon, a broad-coverage grammar of English, semantic verb decompositions, rules mapping between syntactic and semantic constituents, and a donlain model. PUNDIT has been developed cooperatively with the NYU PROTEUS system (Prototype Text Understanding System), These systems are funded by DARPA as part of the I This work is supported in par t by DARPA under cont rac t N00014-85C-0012, administered by the Office of Naval Research. APPROVED FOR PUBLIC RELEASE, DISTRIBUTION UNLIMITED. 2 Prolog UNDders tands In tegra ted Text work in natural language understanding for the Strategic Computing Battle Management Program. The PROTEUS/PUNDIT system will map Navy CASREP's (equipment casualty reports) into a database, which is accessed by an expert system to determine overall fleet readiness. PUNDIT has also been applied to the domain of computer maintenance reports, which is discussed here. The paper focuses on the interaction between the syntactic, semantic and pragmatic modules that is required for the task of making implicit information explicit. We have isolated two types of implicit entities: syntactic entities which are missing syntactic constituents, and semantic entities which are unfilled semantic roles. Some missing entities are optional, and can be ignored. Syntax and semantics have to recognize the OBLIGATORY missing entities and then mark them so that reference resolution knows to find specific referents for those entities, thus making the implicit information explicit. Reference resolution uses two different methods for filling the different types of entities which are also used for general noun phrase reference problems. Implicit syntactic entities, ELIDED CONSTITUENTS, are treated like pronouns, and implicit semantic entities, ESSENTIAL ROLES are treated like definite noun phrases. The pragmatic module as currently implemented consists mainly of a reference resolution component, which is sptflcient for the pragmatic issues described in this paper. We are in the process of adding a time module to handle time issues that have arisen during the analysis of the Navy CASREPS. 2. T h e S y n t a c t i c C o m p o n e n t The syntactic component has three parts: the grammar, a parsing mechanism to execute the grammar, and a lexicon. The grammar consists of context-free BNF definitions (currently nulnbering approximately 80) and associated restrictions (approximately 35). The restrictions enforce contextsensitive welt-formedness constraints and, in some cases, apply optimization strategies to prevent unnecessary structure-building. Each of these three parts is described further below.