Articles

Social media platforms have enabled people to freely express their views and discuss issues of interest with others. While it is important to dis- cover the topics in discussions, it is equally use- ful to mine the nature of such discussions or de- bates and the behavior of the participants. …...

In this paper, we explore the utility of intra- and inter-sentential causal relations between terms or clauses as evidence for answering why-questions. To the best of our knowledge, this is the first work that uses both intra- and inter-sentential causal relations for why-QA. We also propose a method for assessing …...

Unbiased language is a requirement for reference sources like encyclopedias and scientific texts. Bias is, nonetheless, ubiq- uitous, making it crucial to understand its nature and linguistic realization and hence detect bias automatically. To this end we analyze real instances of human edits de- signed to remove bias from Wikipedia …...

This paper addresses the task of fine- grained opinion extraction – the identi- fication of opinion-related entities: the opinion expressions, the opinion hold- ers, and the targets of the opinions, and the relations between opinion expressions and their targets and holders. Most ex- isting approaches tackle the extraction of opinion …...

We propose a joint model for unsuper- vised induction of sentiment, aspect and discourse information and show that by in- corporating a notion of latent discourse re- lations in the model, we improve the pre- diction accuracy for aspect and sentiment polarity on the sub-sentential level. We deviate from the …...

The 2011 Great East Japan Earthquake caused a wide range of problems, and as countermeasures, many aid activities were carried out. Many of these problems and aid activities were reported via Twitter. However, most problem reports and corre- sponding aid messages were not success- fully exchanged between victims and lo- …...

We study question answering as a ma- chine learning problem, and induce a func- tion that maps open-domain questions to queries over a database of web extrac- tions. Given a large, community-authored, question-paraphrase corpus, we demon- strate that it is possible to learn a se- mantic lexicon and linear ranking …...

Procedural dialog systems can help users achieve a wide range of goals. However, such systems are challenging to build, currently requiring manual engineering of substantial domain-specific task knowl- edge and dialog management strategies. In this paper, we demonstrate that it is pos- sible to learn procedural dialog systems given only …...

We propose a method for automatically detecting low-quality Web-text translated by statistical machine translation (SMT) systems. We focus on the phrase salad phenomenon that is observed in existing SMT results and propose a set of computa- tionally inexpensive features to effectively detect such machine-translated sentences from a large-scale Web-mined text. …...

Hiero translation models have two lim- itations compared to phrase-based mod- els: 1) Limited hypothesis space; 2) No lexicalized reordering model. We pro- pose an extension of Hiero called Phrasal- Hiero to address Hiero’s second problem. Phrasal-Hiero still has the same hypoth- esis space as the original Hiero but in- …...

We present a city navigation and tourist information mobile dialogue app with in- tegrated question-answering (QA) and ge- ographic information system (GIS) mod- ules that helps pedestrian users to nav- igate in and learn about urban environ- ments. In contrast to existing mobile apps which treat these problems independently, our …...

We introduce a social media text normal- ization system that can be deployed as a preprocessing step for Machine Transla- tion and various NLP applications to han- dle social media text. The proposed sys- tem is based on unsupervised learning of the normalization equivalences from unla- beled text. The proposed …...

In this paper we address the problem of solving substitution ciphers using a beam search approach. We present a concep- tually consistent and easy to implement method that improves the current state of the art for decipherment of substitution ci- phers and is able to use high order n-gram language …...

Some languages lack large knowledge bases and good discriminative features for Name Entity Recognition (NER) that can general- ize to previously unseen named entities. One such language is Arabic, which: a) lacks a capitalization feature; and b) has relatively small knowledge bases, such as Wikipedia. In this work we address …...

We suggest a generation task that inte- grates discourse-level referring expression generation and sentence-level surface re- alization. We present a data set of Ger- man articles annotated with deep syntax and referents, including some types of im- plicit referents. Our experiments compare several architectures varying the order of a set …...

In this paper, we present a solution to one aspect of the decipherment task: the pre- diction of consonants and vowels for an unknown language and alphabet. Adopt- ing a classical Bayesian perspective, we performs posterior inference over hun- dreds of languages, leveraging knowledge of known languages and alphabets to …...

Speakers of a language can construct an unlimited number of new words through morphological derivation. This is a major cause of data sparseness for corpus-based approaches to lexical semantics, such as distributional semantic models of word meaning. We adapt compositional meth- ods originally developed for phrases to the task of …...

Relation Extraction (RE) is the task of extracting semantic relationships between entities in text. Recent studies on rela- tion extraction are mostly supervised. The clear drawback of supervised methods is the need of training data: labeled data is expensive to obtain, and there is often a mismatch between the training …...

Methods for information extraction (IE) and knowledge base (KB) construction have been intensively studied. However, a largely under-explored case is tapping into highly dynamic sources like news streams and social media, where new entities are continuously emerging. In this paper, we present a method for discovering and se- mantically typing …...

As a paratactic language, sentence-level argument extraction in Chinese suffers much from the frequent occurrence of ellipsis with regard to inter-sentence arguments. To resolve such problem, this paper proposes a novel global argument inference model to explore specific relationships, such as Coreference, Sequence and Parallel, among relevant event mentions to …...