Some Linguistic Aspects for Automatic Text Understanding

2249

Authors

nan

Abstract

This paper proposes a system of map- ping classes of syntactic structures as instruments for automatic text under- standing. The system illustrated in Japa- nese consists of a set of verb classes and information on mapping them together with noun phrases, tense and aspect. The sys- tem. having information on direction of possible inferences between the verb classes with information on tense and as- pect, is supposed to be utilized for rea- soning in automatic text understanding. I.

Keywords

nan

Full Content

SOME LINGUISTIC ASPECTS FOR AUTOMATIC TEXT UNDERSTANDING Yutaka Kusanagi Institute of Literature and Linguistics University of Tsukuba Sakura-mura, Ibarakl 305 JAPAN ABSTRACT This paper proposes a system of map- ping classes of syntactic structures as instruments for automatic text under- standing. The system illustrated in Japa- nese consists of a set of verb classes and information on mapping them together with noun phrases, tense and aspect. The sys- tem. having information on direction of possible inferences between the verb classes with information on tense and as- pect, is supposed to be utilized for rea- soning in automatic text understanding. I. INTRODUCTION The purpose of this paper is to pro- pose a system of mapping classes of syn- tactic structures as instruments for auto- matic text understanding. The system con- sists of a set of verb classes and Jnfor- matlon on mapping them together with noun phrases, tense and aspect, and ]s supposed to he utilized for inference in automatic text understanding. The language used for illustration of the system is Japanese. There Is a tendency for non-syntactic analysers and semantic grammars In auto- matic text understanding. However. this proposal Is motivated by the fact that syntactic structures, once analyzed and classified in terms of semantic related- ness, provide much information for" under- standing. This is supported by the fact that human beings use syntactically re- lated sentences when they ask questions about texts. The system we are proposing has the following elements: 1) Verb classes. 2) Mapping of noun phrases between or among some verb classes. 3) Direction of possible infel'ence between the classes with information on tense and aspect. Our experiment, in which subjects are asked to make true-false questions about certain texts, revealed that native speak- ers think that they understand texts by deducting sentences lexically or semanti- cally related. For instance, a human being relates questions such as 'Did Mary go to a theater?' to a sentence in texts such as 'John took Mary to a theater.' Or, by the same sentence, he understands that 'Mary was in the theater." II. FEATURES OF THE JAPANESE SYNTAX Features of ,Japanese syntax relevant to the discussion in this paper are pre- sented below. The sentence usually ha:# case mark- ings as postpositions to noun phrases. For instance. I. John qa Mary D_J_ himitsu o hanashita 'John told a secret to Mary.' In sentence 1. postpositions ga. ni and o indicate nominative, dative alld accusa- tive. respectively. 409 However. postposJtions do not unique- {y map to deep cases. Take the followitlg sentences for example. 2. John ~ia_ sanii B i_ itta. "John went at :? o'cio(-k.' 3. John w_a Tokyo r!t itta. "John ~,~'ellt to Tokyo." 4. Johr~ w;~ Tokyo ILI :~undeiru. 'John lives in Tokyo.' Ni in the sentences 2, 3. 4 indicate time. goal and location, r e s p e c t i v e l y . This is due to the verb ca|egory (3 and 41 OF the class of noun phrases (2 and 31 …

Content truncated to 500 words

Labeled Text

This paper proposes a system of map- ping classes of syntactic structures as instruments for automatic text under- standing. The system illustrated in Japa- nese consists of a set of verb classes and information on mapping them together with noun phrases, tense and aspect. The sys- tem. having information on direction of possible inferences between the verb classes with information on tense and as- pect, is supposed to be utilized for rea- soning in automatic text understanding. I.

Publication Details

Paper ID:
2249
Year:
1984
Publication:
TIPSTER
Publication Type:
conf
DOI:
nan