We present a two-stage multilingual dependency parsing system submitted to the Multilingual Track of CoNLL-2007. The parser first identifies dependencies using a deterministic p...
Speech recognition transcripts are far from perfect; they are not of sufficient quality to be useful on their own for spoken document retrieval. This is especially the case for c...
In this paper, we consider the computational modelling of human plausibility judgements for verb-relation-argument triples, a task equivalent to the computation of selectional pre...
We present V-measure, an external entropybased cluster evaluation measure. Vmeasure provides an elegant solution to many problems that affect previously defined cluster evaluatio...
We present a domain-independent unsupervised topic segmentation approach based on hybrid document indexing. Lexical chains have been successfully employed to evaluate lexical cohe...
We achieved a state of the art performance in statistical machine translation by using a large number of features with an online large-margin training algorithm. The millions of p...
Taro Watanabe, Jun Suzuki, Hajime Tsukada, Hideki ...
We describe some challenges of adaptation in the 2007 CoNLL Shared Task on Domain Adaptation. Our error analysis for this task suggests that a primary source of error is differenc...
Mark Dredze, John Blitzer, Partha Pratim Talukdar,...
This paper proposes a tree kernel with contextsensitive structured parse tree information for relation extraction. It resolves two critical problems in previous tree kernels for r...
Guodong Zhou, Min Zhang, Dong-Hong Ji, Qiaoming Zh...
We describe a discriminatively trained sequence alignment model based on the averaged perceptron. In common with other approaches to sequence modeling using perceptrons, and in co...
Syntactic reordering approaches are an effective method for handling word-order differences between source and target languages in statistical machine translation (SMT) systems. T...