EMNLP
2007
13 years 9 months ago
2007
This paper compares a deep and a shallow processing approach to the problem of classifying a sentence as grammatically wellformed or ill-formed. The deep processing approach uses ...
EMNLP
2007
13 years 9 months ago
2007
This paper reports on the benefits of largescale statistical language modeling in machine translation. A distributed infrastructure is proposed which we use to train on up to 2 t...
EMNLP
2007
13 years 9 months ago
2007
This paper provides an algorithmic framework for learning statistical models involving directed spanning trees, or equivalently non-projective dependency structures. We show how p...
EMNLP
2007
13 years 9 months ago
2007
Reordering model is important for the statistical machine translation (SMT). Current phrase-based SMT technologies are good at capturing local reordering but not global reordering...
EMNLP
2007
13 years 9 months ago
2007
Semantic inference is a core component of many natural language applications. In response, several researchers have developed algorithms for automatically learning inference rules...
EMNLP
2007
13 years 9 months ago
2007
We present an adaptation of constraint satisfaction inference (Canisius et al., 2006b) for predicting dependency trees. Three different classifiers are trained to predict weighte...
EMNLP
2007
13 years 9 months ago
2007
The technology of opinion extraction allows users to retrieve and analyze people’s opinions scattered over Web documents. We define an opinion unit as a quadruple consisting of...
EMNLP
2007
13 years 9 months ago
2007
In morphologically rich languages, should morphological and syntactic disambiguation be treated sequentially or as a single problem? We describe several efficient, probabilistica...
EMNLP
2007
13 years 9 months ago
2007
In this paper, we describe a new algorithm for recovering WH-trace empty nodes. Our approach combines a set of hand-written patterns together with a probabilistic model. Because t...
EMNLP
2007
13 years 9 months ago
2007
Following (Blitzer et al., 2006), we present an application of structural correspondence learning to non-projective dependency parsing (McDonald et al., 2005). To induce the corre...