Syntax-Driven Sentence Revision for Broadcast News Summarization
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TLDR
It is shown in experiments the method was able to find semantically appropriate revisions thus demonstrating its basic feasibility and that parsing errors mainly degraded the sentential completeness such as grammaticality and redundancy.Abstract:
We propose a method of revising lead sentences in a news broadcast. Unlike many other methods proposed so far, this method does not use the coreference relation of noun phrases (NPs) but rather, insertion and substitution of the phrases modifying the same head chunk in lead and other sentences. The method borrows an idea from the sentence fusion methods and is more general than those using NP coreferencing as ours includes them. We show in experiments the method was able to find semantically appropriate revisions thus demonstrating its basic feasibility. We also show that that parsing errors mainly degraded the sentential completeness such as grammaticality and redundancy.read more
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References
More filters
Journal ArticleDOI
The automatic creation of literature abstracts
TL;DR: In the exploratory research described, the complete text of an article in machine-readable form is scanned by an IBM 704 data-processing machine and analyzed in accordance with a standard program.
Proceedings Article
Applying Conditional Random Fields to Japanese Morphological Analysis
TL;DR: This paper shows how CRFs can be applied to situations where word boundary ambiguity exists, and confirms that CRFs offer a solution to the long-standing problems in corpus-based or statistical Japanese morphological analysis.
Proceedings ArticleDOI
Japanese dependency analysis using cascaded chunking
Taku Kudo,Yuji Matsumoto +1 more
TL;DR: A new statistical Japanese dependency parser using a cascaded chunking model that is simple and efficient, since it parses a sentence deterministically only deciding whether the current segment modifies the segment on its immediate right hand side.
Journal ArticleDOI
Sentence Fusion for Multidocument News Summarization
TL;DR: This article introduces sentence fusion, a novel text-to-text generation technique for synthesizing common information across documents that moves the summarization field from the use of purely extractive methods to the generation of abstracts that contain sentences not found in any of the input documents and can synthesize information across sources.
Proceedings Article
Cut and paste based text summarization
Hongyan Jing,Kathleen R. McKeown +1 more
TL;DR: This work includes a statistically based sentence decomposition program that identifies where the phrases of a summary originate in the original document, producing an aligned corpus of summaries and articles which is used to develop the summarizer.