Articles

We address the grounding of natural lan- guage to concrete spatial constraints, and inference of implicit pragmatics in 3D en- vironments. We apply our approach to the task of text-to-3D scene generation. We present a representation for common sense spatial knowledge and an approach to ex- tract it from 3D …...

Comparisons are common linguistic de- vices used to indicate the likeness of two things. Often, this likeness is not meant in the literal sense—for example, “I slept like a log” does not imply that logs ac- tually sleep. In this paper we propose a computational study of figurative compar- isons, …...

Bridging resolution plays an important role in establishing (local) entity coher- ence. This paper proposes a rule-based approach for the challenging task of unre- stricted bridging resolution, where bridg- ing anaphors are not limited to defi- nite NPs and semantic relations between anaphors and their antecedents are not re- stricted …...

Self-disclosure, the act of revealing one- self to others, is an important social be- havior that strengthens interpersonal rela- tionships and increases social support. Al- though there are many social science stud- ies of self-disclosure, they are based on manual coding of small datasets and ques- tionnaires. We conduct a …...

Latent Dirichlet allocation (LDA) is a topic model that has been applied to var- ious fields, including user profiling and event summarization on Twitter. When LDA is applied to tweet collections, it gen- erally treats all aggregated tweets of a user as a single document. Twitter-LDA, which assumes a single …...

We investigate the interaction of power, gender, and language use in the Enron email corpus. We present a freely avail- able extension to the Enron corpus, with the gender of senders of 87% messages reliably identified. Using this data, we test two specific hypotheses drawn from the sociolinguistic literature pertaining …...

Social media websites provide a platform for anyone to describe significant events taking place in their lives in realtime. Currently, the majority of personal news and life events are published in a tex- tual format, motivating information ex- traction systems that can provide a struc- tured representations of major life …...

We describe an algorithm for automatic clas- sification of idiomatic and literal expressions. Our starting point is that words in a given text segment, such as a paragraph, that are high- ranking representatives of a common topic of discussion are less likely to be a part of an id- iomatic …...

Data-driven refinement of non-terminal categories has been demonstrated to be a reliable technique for improving mono- lingual parsing with PCFGs. In this pa- per, we extend these techniques to learn latent refinements of single-category syn- chronous grammars, so as to improve translation performance. We compare two estimators for this latent-variable …...

Parameter tuning is an important problem in statistical machine translation, but surpris- ingly, most existing methods such as MERT, MIRA and PRO are agnostic about search, while search errors could severely degrade translation quality. We propose a search- aware framework to promote promising par- tial translations, preventing them from be- …...

Distant supervision, a paradigm of rela- tion extraction where training data is cre- ated by aligning facts in a database with a large unannotated corpus, is an attractive approach for training relation extractors. Various models are proposed in recent lit- erature to align the facts in the database to their …...

We address the problem of automatically inferring the tense of events in Chinese text. We use a new corpus annotated with Chinese semantic tense information and other implicit Chinese linguistic informa- tion using a “distant annotation” method. We propose three improvements over a rel- atively strong baseline method – a …...

Information in visually rich formats such as PDF and HTML is often conveyed by a combination of textual and visual features. In particular, genres such as marketing flyers and info-graphics often augment textual information by its color, size, positioning, etc. As a result, tradi- tional text-based approaches to informa- tion …...

Populating Knowledge Base (KB) with new knowledge facts from reliable text re- sources usually consists of linking name mentions to KB entities and identifying relationship between entity pairs. How- ever, the task often suffers from errors propagating from upstream entity linkers to downstream relation extractors. In this paper, we propose …...

Distant supervision has become the lead- ing method for training large-scale rela- tion extractors, with nearly universal adop- tion in recent TAC knowledge-base pop- ulation competitions. However, there are still many questions about the best way to learn such extractors. In this paper we investigate four orthogonal improvements: integrating named …...

Correctly predicting abbreviations given the full forms is important in many natu- ral language processing systems. In this paper we propose a two-stage method to find the corresponding abbreviation given its full form. We first use the contextual information given a large corpus to get ab- breviation candidates for each …...

Open Relation Extraction (ORE) over- comes the limitations of traditional IE techniques, which train individual extrac- tors for every single relation type. Sys- tems such as ReVerb, PATTY, OLLIE, and Exemplar have attracted much attention on English ORE. However, few studies have been reported on ORE for languages beyond English. …...

This paper proposes a history-based struc- tured learning approach that jointly ex- tracts entities and relations in a sentence. We introduce a novel simple and flexible table representation of entities and rela- tions. We investigate several feature set- tings, search orders, and learning meth- ods with inexact search on the …...

The efficiency of Information Extraction systems is known to be heavily influenced by domain-specific knowledge but the cost of developing such systems is consider- ably high. In this article, we consider the problem of event extraction and show that learning word representations from unla- beled domain-specific data and using them …...

We show that semantic relationships can be used to improve word alignment, in ad- dition to the lexical and syntactic features that are typically used. In this paper, we present a method based on a neural net- work to automatically derive word simi- larity from monolingual data. We present an …...