We describe an information extraction system in which four classes of naming expressions organisation, person, location and tinm names are recognised and classified with nearly 92% combined precision and recall. The system applies a mixture of techniques to perform this task and these are described in detail. We have quantitatively evaluated the system against a blind test set of Wall Street Journal business articles and report results not only for the system as a whole, but for each component technique and for each class of name. These results show that in order to have high recall, the system needs to make use not only of information internal to the naming expression but also information from outside the nmne. They also show that the contribution of each system component w~ries fl'om one (:lass of name expression to another.

We describe an ongoing project whose primary aim is to establish the technology of producing closed captions for TV news programs efficiently using natural language processing and speech recognition techniques for the benefit of the hearing impaired in Japan. The project is supported by the Telecommunications Advancement Organisation of Japan with the help of the ministry of Posts and Telecommunications. We propose natural language and speech processing techniques should be used for efficient closed caption production of TV programs. They enable us to summarise TV news texts into captions automatically, and synchronise TV news texts with speech and video automatically. Then the captions are superimposed on the screen. We propose a combination of shallow methods for the summarisation. For all the sentences in the original text, an importance measure is computed based on key words in the text to determine which sentences are important. If some parts of the sentences are judged unimportant, they are shortened or deleted. We also propose keyword pair model for the synchronisation between text and speech.

We describe an ongoing project whose primary aim is to establish the technology of producing closed captions for TV news programs efficiently using natural language processing and speech recognition techniques for the benefit of the hearing impaired in Japan. The project is supported by the Telecommunications Advancement Organisation of Japan with the help of the ministry of Posts and Telecommunications. We propose natural language and speech processing techniques should be used for efficient closed caption production of TV programs. They enable us to summarise TV news texts into captions automatically, and synchronise TV news texts with speech and video automatically. Then the captions are superimposed on the screen. We propose a combination of shallow methods for the summarisation. For all the sentences in the original text, an importance measure is computed based on key words in the text to determine which sentences are important. If some parts of the sentences are judged unimportant, they are shortened or deleted. We also propose keyword pair model for the synchronisation between text and speech.

In this article we outline a basic approach to treating metonymy properly in a multilingual machine translation system. This is the first attempt at treating metonymy in an machine translation environment. The approach is guided by the differences of acceptability of metonymy which were obtained by our comparative survey among three languages, English, Chinese, and Japanese.The characteristics of the approach are as follows:(1) Influences of the context, individuals, and familiality with metonymy are not used. (2) An actual acceptability of each metonymic expression is not realized directly. (3) Grouping metonymic examples into patterns is determined by the acceptability judgement of the speakers surveyed as well as the analysts' intuition. (4) The analysis and generation components treat metonymy differently using the patterns. (5) The analysis component accepts a wider range of metonymy than the actual results of the survey, and the generation component treats metonymy more strictly than the actual results. We think that the approach is a starting point for more sophisticated approaches to translation in a multilirtgual machine translation environment.

name with to (with), kara (from), wo tsuuji (through), tono aidade (between or among).