Articles

Relation classification is an important se- mantic processing task in the field of natu- ral language processing (NLP). In this pa- per, we present a novel model BRCNN to classify the relation of two entities in a sentence. Some state-of-the-art systems concentrate on modeling the shortest de- pendency path (SDP) …...

Neuro-imaging studies on reading differ- ent parts of speech (PoS) report somewhat mixed results, yet some of them indicate different activations with different PoS. This paper addresses the difficulty of using fMRI to discriminate between linguistic tokens in reading of running text because of low temporal resolution. We show that …...

We introduce the Treebank of Learner En- glish (TLE), the first publicly available syntactic treebank for English as a Sec- ond Language (ESL). The TLE provides manually annotated POS tags and Univer- sal Dependency (UD) trees for 5,124 sen- tences from the Cambridge First Certifi- cate in English (FCE) corpus. …...

Digital personal assistants are becoming both more common and more useful. The major NLP challenge for personal assis- tants is machine understanding: translat- ing natural language user commands into an executable representation. This paper focuses on understanding rules written as If-Then statements, though the techniques should be portable to other …...

Automated Text Scoring (ATS) provides a cost-effective and consistent alternative to human marking. However, in order to achieve good performance, the pre- dictive features of the system need to be manually engineered by human ex- perts. We introduce a model that forms word representations by learning the ex- tent to …...

This paper proposes an unsupervised approach for segmenting a multi- author document into authorial com- ponents. The key novelty is that we utilize the sequential patterns hid- den among document elements when determining their authorships. For this purpose, we adopt Hidden Markov Model (HMM) and construct a sequen- tial probabilistic …...

Sentiment Analysis (SA) is an active research area nowadays due to the tremendous interest in aggregating and evaluating opinions being disseminated by users on the Web. SA of English has been thoroughly researched; however research on SA of Arabic has just flourished. Twitter is considered a powerful tool for disseminating …...

Document collections often have links be- tween documents—citations, hyperlinks, or revisions—and which links are added is often based on topical similarity. To model these intuitions, we introduce a new topic model for documents situated within a net- work structure, integrating latent blocks of documents with a max-margin learning criterion for …...

News reader comments found in many on-line news websites are typically massive in amount. We investigate the task of Cultural-common Topic Detection (CTD), which is aimed at discovering common discussion topics from news reader comments written in different languages. We propose a new probabilistic graphical model called MCTA which can …...

Word embedding maps words into a low- dimensional continuous embedding space by exploiting the local word collocation patterns in a small context window. On the other hand, topic modeling maps docu- ments onto a low-dimensional topic space, by utilizing the global word collocation patterns in the same document. These two …...

Properties of corpora, such as the diver- sity of vocabulary and how tightly related texts cluster together, impact the best way to cluster short texts. We examine several such properties in a variety of corpora and track their effects on various combinations of similarity metrics and clustering algo- rithms. We …...

A long-standing challenge in coreference resolution has been the incorporation of entity-level information – features defined over clusters of mentions instead of men- tion pairs. We present a neural net- work based coreference system that pro- duces high-dimensional vector represen- tations for pairs of coreference clusters. Using these representations, our …...

Entity resolution is the task of linking each mention of an entity in text to the cor- responding record in a knowledge base (KB). Coherence models for entity resolu- tion encourage all referring expressions in a document to resolve to entities that are related in the KB. We explore attention- …...

Research on generating referring expres- sions has so far mostly focussed on “one- shot reference”, where the aim is to gener- ate a single, discriminating expression. In interactive settings, however, it is not un- common for reference to be established in “installments”, where referring informa- tion is offered piecewise until …...

Over the past decade, large-scale super- vised learning corpora have enabled ma- chine learning researchers to make sub- stantial advances. However, to this date, there are no large-scale question- answer corpora available. In this paper we present the 30M Factoid Question- Answer Corpus, an enormous question- answer pair corpus produced …...

How much is 131 million US dollars? To help readers put such numbers in con- text, we propose a new task of automati- cally generating short descriptions known as perspectives, e.g. “$131 million is about the cost to employ everyone in Texas over a lunch period”. First, we collect a …...

In this study, we introduce a non- deterministic method for referring expres- sion generation. We describe two models that account for individual variation in the choice of referential form in automatically generated text: a Naive Bayes model and a Recurrent Neural Network. Both are eval- uated using the VaREG corpus. …...

Modeling interactions between two sen- tences is crucial for a number of natu- ral language processing tasks including Answer Selection, Dialogue Act Analy- sis, etc. While deep learning methods like Recurrent Neural Network or Convo- lutional Neural Network have been proved to be powerful for sentence modeling, prior studies paid …...

To establish sophisticated dialogue sys- tems, text planning needs to cope with congruent as well as incongruent inter- locutor interests as given in everyday di- alogues. Little attention has been given to this topic in text planning in contrast to di- alogues that are fully aligned with antic- ipated user …...

The applicability of entropy rate constancy to dialogue is examined on two spoken di- alogue corpora. The principle is found to hold; however, new entropy change pat- terns within the topic episodes of dialogue are described, which are different from written text. Speaker’s dynamic roles as topic initiators and topic …...