We present a global joint model for lemmatization and part-of-speech prediction. Using only morphological lexicons and unlabeled data, we learn a partiallysupervised part-of-speec...
The automatic extraction of relations between entities expressed in natural language text is an important problem for IR and text understanding. In this paper we show how differen...
This paper explores methods to alleviate the effect of lexical sparseness in the classification of verbal arguments. We show how automatically generated selectional preferences ar...
Prior approaches to sentence compression have taken low level syntactic constraints into account in order to maintain grammaticality. We propose and successfully evaluate a more c...
Sourish Chaudhuri, Naman K. Gupta, Noah A. Smith, ...
We present a syntactic and lexically based discourse segmenter (SLSeg) that is designed to avoid the common problem of over-segmenting text. Segmentation is the first step in a di...