This paper presents a new approach to improving relation extraction based on minimally supervised learning. By adding some limited closed-world knowledge for confidence estimation...
Feiyu Xu, Hans Uszkoreit, Sebastian Krause, Hong L...
Temporal expressions in texts contain significant temporal information. Understanding temporal information is very useful in many NLP applications, such as information extraction,...
In this paper we address methodological issues in the evaluation of a projectionbased framework for dependency parsing in which annotations for a source language are transfered to...
Creating correct, semantic representations of questions is essential for applications that can use formal reasoning to answer them. However, even within a restricted domain, it is...
An important task of opinion mining is to extract people's opinions on features of an entity. For example, the sentence, "I love the GPS function of Motorola Droid"...
Lei Zhang, Bing Liu, Suk Hwan Lim, Eamonn O'Brien-...
In this paper, we propose a novel dependency-based bracketing transduction grammar for statistical machine translation, which converts a source sentence into a target dependency t...
Jinsong Su, Yang Liu, Haitao Mi, Hongmei Zhao, Yaj...
We present novel kernels based on structured and unstructured features for reranking the N-best hypotheses of conditional random fields (CRFs) applied to entity extraction. The fo...
Truc-Vien T. Nguyen, Alessandro Moschitti, Giusepp...
Automated identification of diverse sentiment types can be beneficial for many NLP systems such as review summarization and public media analysis. In some of these systems there i...
Annotating scientific publications with keywords and phrases is of great importance to searching, indexing, and cataloging such documents. Unlike previous studies that focused on ...