Articles

We present a new lexical resource for the study of preposition behavior, the Pattern Dictionary of English Prepositions (PDEP). This dictionary, which follows principles laid out in Hanks’ theory of norms and exploita- tions, is linked to 81,509 sentences for 304 prepositions, which have been made available under The Preposition …...

This paper defines a systematic approach to Opinion Mining (OM) on YouTube comments by (i) modeling classifiers for predicting the opinion polarity and the type of comment and (ii) proposing ro- bust shallow syntactic structures for im- proving model adaptability. We rely on the tree kernel technology to automatically ex- …...

Sentence compression has been shown to benefit from joint inference involving both n-gram and dependency-factored objec- tives but this typically requires expensive integer programming. We explore instead the use of Lagrangian relaxation to decou- ple the two subproblems and solve them separately. While dynamic programming is viable for bigram-based sentence …...

We present a novel approach for automatic report generation from time-series data, in the context of student feedback genera- tion. Our proposed methodology treats content selection as a multi-label (ML) classification problem, which takes as in- put time-series data and outputs a set of templates, while capturing the dependen- cies …...

ive Summarization of Spoken and Written Conversations Based on Phrasal Queries Yashar Mehdad Giuseppe Carenini Raymond T. Ng Department of Computer Science, University of British Columbia Vancouver, BC, V6T 1Z4, Canada {mehdad, carenini, rng}@cs.ubc.ca Abstract We propose a novel abstractive query- based summarization system for conversa- tions, where queries are …...

Probabilistic Soft Logic (PSL) is a re- cently developed framework for proba- bilistic logic. We use PSL to combine logical and distributional representations of natural-language meaning, where distri- butional information is represented in the form of weighted inference rules. We ap- ply this framework to the task of Seman- tic …...

Semantic hierarchy construction aims to build structures of concepts linked by hypernym–hyponym (“is-a”) relations. A major challenge for this task is the automatic discovery of such relations. This paper proposes a novel and effec- tive method for the construction of se- mantic hierarchies based on word em- beddings, which can …...

We present an approach to training a joint syntactic and semantic parser that com- bines syntactic training information from CCGbank with semantic training informa- tion from a knowledge base via distant su- pervision. The trained parser produces a full syntactic parse of any sentence, while simultaneously producing logical forms for …...

While automatic keyphrase extraction has been examined extensively, state-of-the- art performance on this task is still much lower than that on many core natural lan- guage processing tasks. We present a sur- vey of the state of the art in automatic keyphrase extraction, examining the major sources of errors made …...

We explore the extent to which high- resource manual annotations such as tree- banks are necessary for the task of se- mantic role labeling (SRL). We examine how performance changes without syntac- tic supervision, comparing both joint and pipelined methods to induce latent syn- tax. This work highlights a new …...

Topic models, an unsupervised technique for inferring translation domains improve machine translation quality. However, pre- vious work uses only the source language and completely ignores the target language, which can disambiguate domains. We pro- pose new polylingual tree-based topic mod- els to extract domain knowledge that con- siders both source …...

Earnings call summarizes the financial performance of a company, and it is an important indicator of the future financial risks of the company. We quantitatively study how earnings calls are correlated with the financial risks, with a special fo- cus on the financial crisis of 2009. In par- ticular, we …...

This paper explores a simple and effec- tive unified framework for incorporating soft linguistic reordering constraints into a hierarchical phrase-based translation sys- tem: 1) a syntactic reordering model that explores reorderings for context free grammar rules; and 2) a semantic re- ordering model that focuses on the re- ordering of …...

Crowdsourcing is a viable mechanism for creating training data for machine trans- lation. It provides a low cost, fast turn- around way of processing large volumes of data. However, when compared to pro- fessional translation, naive collection of translations from non-professionals yields low-quality results. Careful quality con- trol is necessary …...

An individual’s words often reveal their po- litical ideology. Existing automated tech- niques to identify ideology from text focus on bags of words or wordlists, ignoring syn- tax. Taking inspiration from recent work in sentiment analysis that successfully models the compositional aspect of language, we apply a recursive neural network …...

Many machine learning datasets are noisy with a substantial number of mislabeled instances. This noise yields sub-optimal classification performance. In this paper we study a large, low quality annotated dataset, created quickly and cheaply us- ing Amazon Mechanical Turk to crowd- source annotations. We describe compu- tationally cheap feature weighting …...

We present a method to jointly learn fea- tures and weights directly from distri- butional data in a log-linear framework. Specifically, we propose a non-parametric Bayesian model for learning phonologi- cal markedness constraints directly from the distribution of input-output mappings in an Optimality Theory (OT) setting. The model uses an …...

Analyses of filler-gap dependencies usu- ally involve complex syntactic rules or heuristics; however recent results suggest that filler-gap comprehension begins ear- lier than seemingly simpler constructions such as ditransitives or passives. Therefore, this work models filler-gap acquisition as a byproduct of learning word orderings (e.g. SVO vs OSV), which must …...

Learning phonetic categories is one of the first steps to learning a language, yet is hard to do using only distributional phonetic in- formation. Semantics could potentially be useful, since words with different mean- ings have distinct phonetics, but it is un- clear how many word meanings are known to …...

We introduce a novel approach for build- ing language models based on a system- atic, recursive exploration of skip n-gram models which are interpolated using modi- fied Kneser-Ney smoothing. Our approach generalizes language models as it contains the classical interpolation with lower or- der models as a special case. In …...