This paper investigates conceptually and empirically the novel sense matching task, which requires to recognize whether the senses of two synonymous words match in context. We sug...
With performance above 97% accuracy for newspaper text, part of speech (POS) tagging might be considered a solved problem. Previous studies have shown that allowing the parser to ...
In this paper, we will present an efficient method to compute the co-occurrence counts of any pair of substring in a parallel corpus, and an algorithm that make use of these count...
Most approaches to event extraction focus on mentions anchored in verbs. However, many mentions of events surface as noun phrases. Detecting them can increase the recall of event ...
Cassandre Creswell, Matthew J. Beal, John Chen, Th...
We present an algorithm for automatically disambiguating noun-noun compounds by deducing the correct semantic relation between their constituent words. This algorithm uses a corpu...
We consider the problem of producing a multi-document summary given a collection of documents. Since most successful methods of multi-document summarization are still largely extr...
John M. Conroy, Judith D. Schlesinger, Dianne P. O...
Semantic parsing is the task of mapping natural language sentences to complete formal meaning representations. The performance of semantic parsing can be potentially improved by u...
Sentence compression is the task of producing a summary at the sentence level. This paper focuses on three aspects of this task which have not received detailed treatment in the l...
This work provides the essential foundations for modular construction of (typed) unification grammars for natural languages. Much of the information in such grammars is encoded in...
The ability to compress sentences while preserving their grammaticality and most of their meaning has recently received much attention. Our work views sentence compression as an o...