Articles

In this paper we develop a story genera- tor that leverages knowledge inherent in corpora without requiring extensive man- ual involvement. A key feature in our ap- proach is the reliance on a story planner which we acquire automatically by record- ing events, their participants, and their precedence relationships in …...

Word Sense Disambiguation remains one of the most complex problems facing com- putational linguists to date. In this pa- per we present a system that combines evidence from a monolingual WSD sys- tem together with that from a multilingual WSD system to yield state of the art per- formance on …...

Most previous work on trainable language generation has focused on two paradigms: (a) using a statistical model to rank a set of generated utterances, or (b) using statistics to inform the generation deci- sion process. Both approaches rely on the existence of a handcrafted generator, which limits their scalability to …...

We present a discriminative model that di- rectly predicts which set of phrasal transla- tion rules should be extracted from a sen- tence pair. Our model scores extraction sets: nested collections of all the overlap- ping phrase pairs consistent with an under- lying word alignment. Extraction set mod- els provide …...

In spite of decades of research on word sense disambiguation (WSD), all-words general purpose WSD has remained a dis- tant goal. Many supervised WSD systems have been built, but the effort of creat- ing the training corpus - annotated sense marked corpora - has always been a matter of concern. …...

One of the main obstacles to high- performance Word Sense Disambigua- tion (WSD) is the knowledge acquisi- tion bottleneck. In this paper, we present a methodology to automatically extend WordNet with large amounts of seman- tic relations from an encyclopedic re- source, namely Wikipedia. We show that, when provided with …...

Constructing an encoding of a concept lat- tice using short bit vectors allows for ef- ficient computation of join operations on the lattice. Join is the central operation any unification-based parser must support. We extend the traditional bit vector encod- ing, which represents join failure using the zero vector, to …...

We consider the search for a maximum likelihood assignment of hidden deriva- tions and grammar weights for a proba- bilistic context-free grammar, the problem approximately solved by “Viterbi train- ing.” We show that solving and even ap- proximating Viterbi training for PCFGs is NP-hard. We motivate the use of uniform- …...

Finding a class of structures that is rich enough for adequate linguistic represen- tation yet restricted enough for efficient computational processing is an important problem for dependency parsing. In this paper, we present a transition system for 2-planar dependency trees – trees that can be decomposed into at most two …...

A challenging problem in open informa- tion extraction and text mining is the learn- ing of the selectional restrictions of se- mantic relations. We propose a mini- mally supervised bootstrapping algorithm that uses a single seed and a recursive lexico-syntactic pattern to learn the ar- guments and the supertypes of …...

Graph-based semi-supervised learning (SSL) algorithms have been successfully used to extract class-instance pairs from large unstructured and structured text col- lections. However, a careful comparison of different graph-based SSL algorithms on that task has been lacking. We com- pare three graph-based SSL algorithms for class-instance acquisition on a variety of …...

Statistical translation models that try to capture the recursive structure of language have been widely adopted over the last few years. These models make use of vary- ing amounts of information from linguis- tic theory: some use none at all, some use information about the grammar of the tar- get …...

Weblogs are a source of human activity know- ledge comprising valuable information such as facts, opinions and personal experiences. In this paper, we propose a method for mining personal experiences from a large set of web- logs. We define experience as knowledge em- bedded in a collection of activities or …...

Tree-to-string systems (and their forest- based extensions) have gained steady pop- ularity thanks to their simplicity and effi- ciency, but there is a major limitation: they are unable to guarantee the grammatical- ity of the output, which is explicitly mod- eled in string-to-tree systems via target- side syntax. We thus …...

This paper explores the effect that dif- ferent corpus configurations have on the performance of a coreference resolution system, as measured by MUC, B3, and CEAF. By varying separately three param- eters (language, annotation scheme, and preprocessing information) and applying the same coreference resolution system, the strong bonds between system …...

This paper examines how a new class of nonparametric Bayesian models can be ef- fectively applied to an open-domain event coreference task. Designed with the pur- pose of clustering complex linguistic ob- jects, these models consider a potentially infinite number of features and categorical outcomes. The evaluation performed for solving …...

The research focus of computational coreference resolution has exhibited a shift from heuristic approaches to machine learning approaches in the past decade. This paper surveys the major milestones in supervised coreference research since its inception fifteen years ago. 1...

Most sentiment analysis approaches use as baseline a support vector machines (SVM) classifier with binary unigram weights. In this paper, we explore whether more sophisticated feature weighting schemes from Information Retrieval can enhance classification accuracy. We show that vari- ants of the classic tf.idf scheme adapted to sentiment analysis provide …...

There is a growing research interest in opinion retrieval as on-line users’ opinions are becom- ing more and more popular in business, social networks, etc. Practically speaking, the goal of opinion retrieval is to retrieve documents, which entail opinions or comments, relevant to a target subject specified by the user’s …...

In a previous work of ours Chinnakotla et al. (2010) we introduced a novel framework for Pseudo-Relevance Feed- back (PRF) called MultiPRF. Given a query in one language called Source, we used English as the Assisting Language to improve the performance of PRF for the source language. MulitiPRF showed re- …...