Relation triples produced by open domain information extraction (open IE) systems are useful for question answering, inference, and other IE tasks. Traditionally these are extract...
Gabor Angeli, Melvin Jose Johnson Premkumar, Chris...
In this paper, we introduce a new method for the problem of unsupervised dependency parsing. Most current approaches are based on generative models. Learning the parameters of suc...
This paper studies the use of structural representations for learning relations between pairs of short texts (e.g., sentences or paragraphs) of the kind: the second text answers t...
Simone Filice, Giovanni Da San Martino, Alessandro...
We present the Visual Entity Explorer (VEX), an interactive tool for visually exploring and analyzing the output of entity linking systems. VEX is designed to aid developers in im...
In this article, we discuss the challenges of document summarization for the blind and visually impaired people and then propose a new system called BrailleSUM to produce better s...
The goal of this research is to build a model to predict stock price movement using sentiments on social media. A new feature which captures topics and their sentiments simultaneo...
We present a novel scheme for wordbased Japanese typed dependency parser which integrates syntactic structure analysis and grammatical function analysis such as predicate-argument...
We reduce phrase-based parsing to dependency parsing. Our reduction is grounded on a new intermediate representation, “head-ordered dependency trees,” shown to be isomorphic t...
This paper investigates the problem of cross-lingual dependency parsing, aiming at inducing dependency parsers for low-resource languages while using only training data from a res...
Jiang Guo, Wanxiang Che, David Yarowsky, Haifeng W...