We describe a novel method for the task of unsupervised POS tagging with a dictionary, one that uses integer programming to explicitly search for the smallest model that explains ...
We present a graph-based semi-supervised learning for the question-answering (QA) task for ranking candidate sentences. Using textual entailment analysis, we obtain entailment sco...
Supervised sequence-labeling systems in natural language processing often suffer from data sparsity because they use word types as features in their prediction tasks. Consequently...
This paper introduces a new algorithm to parse discourse within the framework of Rhetorical Structure Theory (RST). Our method is based on recent advances in the field of statisti...
Recent work on temporal relation identification has focused on three types of relations between events: temporal relations between an event and a time expression, between a pair o...
Katsumasa Yoshikawa, Sebastian Riedel, Masayuki As...
In this paper, we propose a novel method for semi-supervised learning of nonprojective log-linear dependency parsers using directly expressed linguistic prior knowledge (e.g. a no...
Cross-lingual tasks are especially difficult due to the compounding effect of errors in language processing and errors in machine translation (MT). In this paper, we present an er...
Kristen Parton, Kathleen McKeown, Bob Coyne, Mona ...
It is usually assumed that the kind of noise existing in annotated data is random classification noise. Yet there is evidence that differences between annotators are not always ra...
This paper presents a model for summarizing multiple untranscribed spoken documents. Without assuming the availability of transcripts, the model modifies a recently proposed unsup...
An important and well-studied problem is the production of semantic lexicons from a large corpus. In this paper, we present a system named ASIA (Automatic Set Instance Acquirer), ...