Obtaining labeled data is a significant obstacle for many NLP tasks. Recently, online games have been proposed as a new way of obtaining labeled data; games attract users by being...
David Vickrey, Aaron Bronzan, William Choi, Aman K...
We consider a parsed text corpus as an instance of a labelled directed graph, where nodes represent words and weighted directed edges represent the syntactic relations between the...
We present a generative model for unsupervised coreference resolution that views coreference as an EM clustering process. For comparison purposes, we revisit Haghighi and Klein...
Most attempts to integrate FrameNet in NLP systems have so far failed because of its limited coverage. In this paper, we investigate the applicability of distributional and WordNe...
Marco Pennacchiotti, Diego De Cao, Roberto Basili,...
String-to-string transduction is a central problem in computational linguistics and natural language processing. It occurs in tasks as diverse as name transliteration, spelling co...
Contradiction Detection (CD) in text is a difficult NLP task. We investigate CD over functions (e.g., BornIn(Person)=Place), and present a domain-independent algorithm that automa...
Alan Ritter, Stephen Soderland, Doug Downey, Oren ...
This paper explores the use of set expansion (SE) to improve question answering (QA) when the expected answer is a list of entities belonging to a certain class. Given a small set...
Richard C. Wang, Nico Schlaefer, William W. Cohen,...
Syntactic word reordering is essential for translations across different grammar structures between syntactically distant languagepairs. In this paper, we propose to embed local a...
This paper presents a graph-theoretic model of the acquisition of lexical syntactic representations. The representations the model learns are non-categorical or graded. We propose...
NLP tasks are often domain specific, yet systems can learn behaviors across multiple domains. We develop a new multi-domain online learning framework based on parameter combinatio...