Articles

The definition of combinatory categorial grammar (CCG) in the literature varies quite a bit from author to author. How- ever, the differences between the defini- tions are important in terms of the lan- guage classes of each CCG. We prove that a wide range of CCGs are strongly context-free, including …...

We propose Bilingual Tree Kernels (BTKs) to capture the structural similarities across a pair of syntactic translational equivalences and apply BTKs to sub-tree alignment along with some plain features. Our study reveals that the struc- tural features embedded in a bilingual parse tree pair are very effective for sub-tree alignment …...

While Inversion Transduction Grammar (ITG) has regained more and more attention in recent years, it still suffers from the major obstacle of speed. We propose a discriminative ITG prun- ing framework using Minimum Error Rate Training and various features from previous work on ITG alignment. Experiment results show that it …...

Extracting knowledge from unstructured text is a long-standing goal of NLP. Al- though learning approaches to many of its subtasks have been developed (e.g., pars- ing, taxonomy induction, information ex- traction), all end-to-end solutions to date require heavy supervision and/or manual engineering, limiting their scope and scal- ability. We present …...

Many researchers are trying to use information extraction (IE) to create large-scale knowl- edge bases from natural language text on the Web. However, the primary approach (su- pervised learning of relation-specific extrac- tors) requires manually-labeled training data for each relation and doesn’t scale to the thou- sands of relations encoded …...

This research explores the idea of inducing domain-specific semantic class taggers us- ing only a domain-specific text collection and seed words. The learning process be- gins by inducing a classifier that only has access to contextual features, forcing it to generalize beyond the seeds. The contex- tual classifier then labels …...

This paper explores the use of clickthrough data for query spelling correction. First, large amounts of query-correction pairs are derived by analyzing users' query reformulation behavior encoded in the clickthrough data. Then, a phrase-based error model that accounts for the transformation probability between multi-term phrases is trained and integrated into …...

The variety of engaging interactions among users in social medial distinguishes it from traditional Web media. Such a fea- ture should be utilized while attempting to provide intelligent services to social me- dia participants. In this article, we present a framework to recommend relevant infor- mation in Internet forums and …...

Existing word similarity measures are not robust to data sparseness since they rely only on the point estimation of words’ context profiles obtained from a limited amount of data. This paper proposes a Bayesian method for robust distributional word similarities. The method uses a dis- tribution of context profiles obtained …...

Current Semantic Role Labeling technolo- gies are based on inductive algorithms trained over large scale repositories of annotated examples. Frame-based sys- tems currently make use of the FrameNet database but fail to show suitable general- ization capabilities in out-of-domain sce- narios. In this paper, a state-of-art system for frame-based SRL …...

The core-adjunct argument distinction is a basic one in the theory of argument struc- ture. The task of distinguishing between the two has strong relations to various ba- sic NLP tasks such as syntactic parsing, semantic role labeling and subcategoriza- tion acquisition. This paper presents a novel unsupervised algorithm for …...

In this paper we present BabelNet – a very large, wide-coverage multilingual se- mantic network. The resource is automat- ically constructed by means of a method- ology that integrates lexicographic and en- cyclopedic knowledge from WordNet and Wikipedia. In addition Machine Transla- tion is also applied to enrich the resource …...

Tree-to-string translation rules are widely used in linguistically syntax-based statis- tical machine translation systems. In this paper, we propose to use deep syntac- tic information for obtaining fine-grained translation rules. A head-driven phrase structure grammar (HPSG) parser is used to obtain the deep syntactic information, which includes a fine-grained description …...

The analysis of reading times can pro- vide insights into the processes that under- lie language comprehension, with longer reading times indicating greater cognitive load. There is evidence that the language processor is highly predictive, such that prior context allows upcoming linguistic material to be anticipated. Previous work has investigated …...

Current turn-taking approaches for spoken dialogue systems rely on the speaker re- leasing the turn before the other can take it. This reliance results in restricted interac- tions that can lead to inefficient dialogues. In this paper we present a model we re- fer to as Importance-Driven Turn-Bidding that treats …...

Texts and dialogues often express infor- mation indirectly. For instance, speak- ers’ answers to yes/no questions do not always straightforwardly convey a ‘yes’ or ‘no’ answer. The intended reply is clear in some cases (Was it good? It was great!) but uncertain in others (Was it acceptable? It was unprecedented.). …...

We present a simple yet powerful hier- archical search algorithm for automatic word alignment. Our algorithm induces a forest of alignments from which we can efficiently extract a ranked k-best list. We score a given alignment within the forest with a flexible, linear discrimina- tive model incorporating hundreds of fea- …...

One goal of natural language generation is to produce coherent text that presents in- formation in a logical order. In this pa- per, we show that topological fields, which model high-level clausal structure, are an important component of local coherence in German. First, we show in a sen- tence ordering …...

The pipeline of most Phrase-Based Statistical Machine Translation (PB-SMT) systems starts from automatically word aligned parallel cor- pus. But word appears to be too fine-grained in some cases such as non-compositional phrasal equivalences, where no clear word alignments exist. Using words as inputs to PB- SMT pipeline has inborn deficiency. …...

We present a method for extracting so- cial networks from literature, namely, nineteenth-century British novels and se- rials. We derive the networks from di- alogue interactions, and thus our method depends on the ability to determine when two characters are in conversation. Our approach involves character name chunk- ing, quoted …...