Computer method for identifying predicate-argument structures in natural language text

• US 5,146,406 A
• Filed: 08/16/1989
• Issued: 09/08/1992
• Est. Priority Date: 08/16/1989
• Status: Expired due to Fees

• Current Assignee: International Business Machines Corporation
• Original Assignee: International Business Machines Corporation
• Inventors: Jensen, Karen
• Primary Examiner(s): Shaw, Dale M.
• Assistant Examiner(s): Chung, Xuong
• Application Number:
  US07/395,118
• Time in Patent Office: 1,119 Days
• Field of Search: 364/419, 364/900 MS File, 364/200 MS File
• US Class Current: 704/9
• CPC Class Codes: G06F 40/211 Syntactic parsing, e.g. based on context-free grammar [CFG] or unification grammars
• CPC Class Codes: G06F 40/253 Grammatical analysis; Style critique
• CPC Class Codes: G06F 40/268 Morphological analysis
• CPC Class Codes: G06F 40/30 Semantic analysis

Abstract

A computer method is disclosed for determining predicate-argument structures in input prose sentences of English. The input sentence, in the form of a string of words separated by blanks, is first analyzed (parsed) by a rule component that has access only to morphological and syntactic information about the words. The output of this rule component, in the form of a data structure consisting of attribute-value pairs, is then processed by the argument structure component, which consists of a set of partially ordered procedures that incorporate further linguistic knowledge. The output of these procedures is the same attribute-value structure, now enhanced by the presence of semantic (i.e. meaningful, non-syntactic) attributes. These semantic attributes, taken together, form the argument structure of the input sentence.

The resulting invention constitutes a fully modular, comprehensive and efficient method for passing from syntax to the first stage of semantic processing of natural (human) language. The invention applies to all prose sentences of the language for which it is designed, and not just to a subset of those sentences. It does not use domain-specific semantic information to improve the accuracy or efficiency of the syntactic component. It therefore constitutes an unrestricted broad-coverage method for natural language processing (NLP), as opposed to the restricted methods used in most NLP applications today.

Although the specific rules and procedures will be different for different natural languages, the general concept embodied in this invention is applicable to all natural languages.

Claims

1. In a computer method for determining basic semantic structures for natural language word strings, including inputting a string consisting of a plurality of words forming a linguistic expression in a natural language and parsing the input string with a syntactic set of rules to derive a syntactic structure for the string, identifying syntactic arguments for said words, the method comprising the steps of:

identifying a first group of words in said string as semantic arguments, when said semantic arguments correspond exactly to said syntactic arguments;

identifying semantic arguments in a second group of words in said string, which are not in said first group, by the following steps;

assigning missing arguments of infinitive clauses and participle clauses;

assigning long distance arguments;

assigning missing or displaced arguments in passive constructions;

assigning arguments for indirect object construction;

linking predicate adjectives to their subject noun phrases;

linking verb phrase modifiers to their verbs;

linking noun phrase modifiers to their nouns;

linking adjective phrase modifiers to their adjectives;

linking adverb phrase modifiers to their adverbs;

outputting said assigned arguments in a record which provides a normalized semantic structure for said input word string. PG,26

2. A computer method for determining semantic structures according to claim 1, wherein said normalized semantic structure is achieved by adding new attributes and values having semantic significance, to said syntactic structure.