Articles

In this paper, we argue that n-gram lan- guage models are not sufficient to address word reordering required for Machine Trans- lation. We propose a new distortion model that can be used with existing phrase-based SMT decoders to address those n-gram lan- guage model limitations. We present empirical results in …...

Short vowels and other diacritics are not part of written Arabic scripts. Exceptions are made for important political and reli- gious texts and in scripts for beginning stu- dents of Arabic. Script without diacritics have considerable ambiguity because many words with different diacritic patterns ap- pear identical in a diacritic-less …...

For many years, statistical machine trans- lation relied on generative models to pro- vide bilingual word alignments. In 2005, several independent efforts showed that discriminative models could be used to enhance or replace the standard genera- tive approach. Building on this work, we demonstrate substantial improvement in word-alignment accuracy, partly …...

We present an algorithm which creates a German CCGbank by translating the syn- tax graphs in the German Tiger corpus into CCG derivation trees. The resulting cor- pus contains 46,628 derivations, covering 95% of all complete sentences in Tiger. Lexicons extracted from this corpus con- tain correct lexical entries for …...

This paper describes the development of QuestionBank, a corpus of 4000 parse- annotated questions for (i) use in training parsers employed in QA, and (ii) evalua- tion of question parsing. We present a se- ries of experiments to investigate the ef- fectiveness of QuestionBank as both an exclusive and supplementary …...

We propose a novel reordering model for phrase-based statistical machine transla- tion (SMT) that uses a maximum entropy (MaxEnt) model to predicate reorderings of neighbor blocks (phrase pairs). The model provides content-dependent, hier- archical phrasal reordering with general- ization based on features automatically learned from a real-world bitext. We present …...

This paper presents a new web mining scheme for parallel data acquisition. Based on the Document Object Model (DOM), a web page is represented as a DOM tree. Then a DOM tree alignment model is proposed to identify the transla- tionally equivalent texts and hyperlinks between two parallel DOM trees. …...

Hidden Markov models (HMMs) are pow- erful statistical models that have found successful applications in Information Ex- traction (IE). In current approaches to ap- plying HMMs to IE, an HMM is used to model text at the document level. This modelling might cause undesired redun- dancy in extraction in the …...

As natural language understanding re- search advances towards deeper knowledge modeling, the tasks become more and more complex: we are interested in more nu- anced word characteristics, more linguistic properties, deeper semantic and syntactic features. One such example, explored in this article, is the mention detection and recognition task in …...

This paper presents techniques to apply semi-CRFs to Named Entity Recognition tasks with a tractable computational cost. Our framework can handle an NER task that has long named entities and many labels which increase the computational cost. To reduce the computational cost, we propose two techniques: the first is the …...

This paper investigates conceptually and empirically the novel sense matching task, which requires to recognize whether the senses of two synonymous words match in context. We suggest direct approaches to the problem, which avoid the intermediate step of explicit word sense disambigua- tion, and demonstrate their appealing ad- vantages and …...

This paper presents a new approach based on Equivalent Pseudowords (EPs) to tackle Word Sense Disambiguation (WSD) in Chinese language. EPs are par- ticular artificial ambiguous words, which can be used to realize unsupervised WSD. A Bayesian classifier is implemented to test the efficacy of the EP solution on Senseval-3 …...

Partial cognates are pairs of words in two languages that have the same meaning in some, but not all contexts. Detecting the actual meaning of a partial cognate in context can be useful for Machine Trans- lation tools and for Computer-Assisted Language Learning tools. In this paper we propose a …...

We present an automatic approach to tree annota- tion in which basic nonterminal symbols are alter- nately split and merged to maximize the likelihood of a training treebank. Starting with a simple X- bar grammar, we learn a new grammar whose non- terminals are subsymbols of the original nontermi- nals. …...

The psycholinguistic literature provides evidence for syntactic priming, i.e., the tendency to repeat structures. This pa- per describes a method for incorporating priming into an incremental probabilis- tic parser. Three models are compared, which involve priming of rules between sentences, within sentences, and within coordinate structures. These models sim- ulate …...

In this paper we define a novel similarity measure between examples of textual en- tailments and we use it as a kernel func- tion in Support Vector Machines (SVMs). This allows us to automatically learn the rewrite rules that describe a non trivial set of entailment cases. The experiments with …...

We present an efficient algorithm for the redundancy elimination problem: Given an underspecified semantic representation (USR) of a scope ambiguity, compute an USR with fewer mutually equivalent read- ings. The algorithm operates on underspec- ified chart representations which are de- rived from dominance graphs; it can be ap- plied to …...

We have constructed a corpus of news ar- ticles in which events are annotated for estimated bounds on their duration. Here we describe a method for measuring in- ter-annotator agreement for these event duration distributions. We then show that machine learning techniques applied to this data yield coarse-grained event dura- …...

Ordering information is a difficult but important task for applications generat- ing natural-language text. We present a bottom-up approach to arranging sen- tences extracted for multi-document sum- marization. To capture the association and order of two textual segments (eg, sen- tences), we define four criteria, chronol- ogy, topical-closeness, precedence, and …...

Sentence compression is the task of pro- ducing a summary at the sentence level. This paper focuses on three aspects of this task which have not received de- tailed treatment in the literature: train- ing requirements, scalability, and auto- matic evaluation. We provide a novel com- parison between a supervised …...