Patent Document ID: 5479563
Application ID: 08174629

Base Claim:
1. An intra-sentence boundary extracting system for extracting a boundary in a structure of a sentence located either before or after a target word included in words forming inputted sentence data, said system comprising: inputted word classifying means for classifying a first number of words forming the inputted sentence data to produce an input pattern indicating a second number of classification results of the words; and boundary position data output means for receiving the classification results from said inputted word classifying means and for outputting at least one of clause and phrase boundary position data, said boundary position data output means including a neural network formed of an input layer having a third number of units, each unit coupled to said inputted word classifying means to receive each part of the input pattern for the first number of words including the target word, n preceding words before the target word and m succeeding words after the target word, where n and m are at least one, the third number corresponding to the first number times the second number of classification results of the words; more than one intermediate layer coupled to said input layer; and an output layer, coupled to at least one of said more than one intermediate layer, to output the boundary position data on the structure of the sentence, corresponding to a boundary of at least one of a clause, a noun phrase, a verb phrase, a preposition phrase and an infinitive phrase either before or after the target word.

---

Claim 5:
5. An intra-sentence boundary extracting system according to claim 1, wherein said inputted word classifying means comprises: a word dictionary for storing part-of-speech numbers representing respective parts of speech; and a part-of-speech number selecting unit for selecting and using from said word dictionary, each part-of-speech number representing one of the words forming the inputted sentence data, and then outputting the part-of-speech number as the classification results for each of the words.