Summarization: an Application for NL Generation
Beryl Hoffman · 1996
this paper, I will be exploring techniques for automatically summarising texts, concentrating on selecting the content of the summary from a parsed (semantic) representation of the original text. Summarization is a particularly nice application for natural language generation because the original text can serve as the knowledge base for generating the summary. In addition, we only need to develop a lexicon limited to the words and senses in the original text (as long as we use the same words in the same context as the original text). This simplifies the generation task somewhat. However, summarization is not a trivial task. We must first analyze the original text using a robust grammar that can produce a reliable semantic interpretation of the text. To simplify this investigation, I will not tackle the many problems of NL analysis, but will use already parsed texts from the TAG Tree Bank (UPenn, 1995). I use a perl script to convert the syntactic structures in this parsed corpus into a list of logical forms that roughly indicate the predicate-argument structure of each clause in the text.