Articles

Identifying mathematical relations expressed in text is essential to understanding a broad range of natural language text from election reports, to financial news, to sport commen- taries to mathematical word problems. This paper focuses on identifying and understand- ing mathematical relations described within a single sentence. We introduce the problem …...

We present a novel semi-supervised approach for sequence transduction and apply it to se- mantic parsing. The unsupervised component is based on a generative model in which latent sentences generate the unpaired logical forms. We apply this method to a number of semantic parsing tasks focusing on domains with lim- …...

Essay scoring is a complicated processing re- quiring analyzing, summarizing and judging expertise. Traditional work on essay scoring focused on automatic handcrafted features, which are expensive yet sparse. Neural mod- els offer a way to learn syntactic and semantic features automatically, which can potentially improve upon discrete features. In this …...

Lexical simplification of scientific terms rep- resents a unique challenge due to the lack of a standard parallel corpora and fast rate at which vocabulary shift along with research. We in- troduce SimpleScience, a lexical simplifica- tion approach for scientific terminology. We use word embeddings to extract simplification rules from …...

Word embedding models learn vectorial word representations that can be used in a variety of NLP applications. When training data is scarce, these models risk losing their gener- alization abilities due to the complexity of the models and the overfitting to finite data. We propose a regularized embedding formu- lation, …...

Though dialectal language is increasingly abundant on social media, few resources exist for developing NLP tools to handle such lan- guage. We conduct a case study of dialectal language in online conversational text by in- vestigating African-American English (AAE) on Twitter. We propose a distantly supervised model to identify AAE-like …...

This paper presents a two-step procedure to extract positive meaning from verbal negation. We first generate potential positive interpre- tations manipulating syntactic dependencies. Then, we score them according to their like- lihood. Manual annotations show that posi- tive interpretations are ubiquitous and intuitive to humans. Experimental results show that dependencies …...

Even syntactically correct sentences are per- ceived as awkward if they do not contain cor- rect punctuation. Still, the problem of au- tomatic generation of punctuation marks has been largely neglected for a long time. We present a novel model that introduces punc- tuation marks into raw text material with …...

This paper presents an approach to extract implicit interpretations from modal construc- tions. Importantly, our approach uses a de- terministic procedure to normalize eventuali- ties and generate potential interpretations. An annotation effort demonstrates that these in- terpretations are intuitive to humans and most modal constructions convey at least one inter- …...

In this paper, we describe our approach of en- abling an interactive dialogue system to rec- ognize user emotion and sentiment in real- time. These modules allow otherwise con- ventional dialogue systems to have “empathy” and answer to the user while being aware of their emotion and intent. Emotion recognition …...

This work investigates style and topic aspects of language in online communities: looking at both utility as an identifier of the commu- nity and correlation with community reception of content. Style is characterized using a hy- brid word and part-of-speech tag n-gram lan- guage model, while topic is represented using …...

Joint dependency parsing with disfluency de- tection is an important task in speech lan- guage processing. Recent methods show high performance for this task, although most au- thors make the unrealistic assumption that in- put texts are transcribed by human annota- tors. In real-world applications, the input text is typically …...

Meaning Representation Sho Takase† Jun Suzuki‡ Naoaki Okazaki† Tsutomu Hirao‡ Masaaki Nagata‡ Graduate School of Information Sciences, Tohoku University† NTT Communication Science Laboratories, NTT Corporation‡ {takase, okazaki}@ecei.tohoku.ac.jp {suzuki.jun, hirao.tsutomu, nagata.masaaki}@lab.ntt.co.jp Abstract Neural network-based encoder-decoder mod- els are among recent attractive methodologies for tackling natural language generation tasks. This paper investigates …...

Supervised stance classification, in such do- mains as Congressional debates and online forums, has been a topic of interest in the past decade. Approaches have evolved from text classification to structured output predic- tion, including collective classification and se- quence labeling. In this work, we investigate collective classification of stances …...

Opinion mining from customer reviews has become pervasive in recent years. Sentences in reviews, however, are usually classified in- dependently, even though they form part of a review’s argumentative structure. Intuitively, sentences in a review build and elaborate upon each other; knowledge of the review struc- ture and sentential context …...

Semantic error detection and correction is an important task for applications such as fact checking, speech-to-text or grammatical er- ror correction. Current approaches gener- ally focus on relatively shallow semantics and do not account for numeric quantities. Our approach uses language models grounded in numbers within the text. Such groundings …...

Annotation projection based on parallel cor- pora has shown great promise in inexpensively creating Proposition Banks for languages for which high-quality parallel corpora and syn- tactic parsers are available. In this paper, we present an experimental study where we ap- ply this approach to three languages that lack such resources: …...

When considering a social media corpus, we often have access to structural information about how messages are flowing between peo- ple or organizations. This information is par- ticularly useful when the linguistic evidence is sparse, incomplete, or of dubious quality. In this paper we construct a simple model to leverage …...

We argue that NLP researchers are especially well-positioned to contribute to the national discussion about gun violence. Reasoning about the causes and outcomes of gun violence is typically dominated by politics and emo- tion, and data-driven research on the topic is stymied by a shortage of data and a lack …...

This paper makes a simple increment to state-of- the-art in sarcasm detection research. Existing ap- proaches are unable to capture subtle forms of con- text incongruity which lies at the heart of sarcasm. We explore if prior work can be enhanced using se- mantic similarity/discordance between word embed- dings. We …...