Articles

Bilingual lexicons are fundamental re- sources. Modern automated lexicon gen- eration methods usually require parallel corpora, which are not available for most language pairs. Lexicons can be gener- ated using non-parallel corpora or a pivot language, but such lexicons are noisy. We present an algorithm for generating a high quality …...

As described in this paper, we propose a new automatic evaluation method for machine translation using noun-phrase chunking. Our method correctly deter- mines the matching words between two sentences using corresponding noun phrases. Moreover, our method deter- mines the similarity between two sen- tences in terms of the noun-phrase or- …...

We present a grand challenge to build a corpus that will include all of the world’s languages, in a consistent structure that permits large-scale cross-linguistic pro- cessing, enabling the study of universal linguistics. The focal data types, bilin- gual texts and lexicons, relate each lan- guage to one of a …...

Once released, treebanks tend to remain unchanged despite any shortcomings in their depth of linguistic analysis or cover- age of specific phenomena. Instead, sepa- rate resources are created to address such problems. In this paper we show how to improve the quality of a treebank, by in- tegrating resources and …...

In this paper, we formulate extractive summarization as a risk minimization problem and propose a unified probabilis- tic framework that naturally combines su- pervised and unsupervised summarization models to inherit their individual merits as well as to overcome their inherent limita- tions. In addition, the...

As information extraction (IE) becomes more central to enterprise applications, rule-based IE engines have become in- creasingly important. In this paper, we describe SystemT, a rule-based IE sys- tem whose basic design removes the ex- pressivity and performance limitations of current systems based on cascading gram- mars. SystemT uses a …...

We present a data-driven approach to learn user-adaptive referring expression gener- ation (REG) policies for spoken dialogue systems. Referring expressions can be dif- ficult to understand in technical domains where users may not know the techni- cal ‘jargon’ names of the domain entities. In such cases, dialogue systems must be …...

Information-extraction (IE) systems seek to distill semantic relations from natural- language text, but most systems use super- vised learning of relation-specific examples and are thus limited by the availability of training data. Open IE systems such as TextRunner, on the other hand, aim to handle the unbounded number of relations …...

We introduce a novel mechanism for incorporating articulatory dynamics into speech recognition with the theory of task dynamics. This system reranks sentence- level hypotheses by the likelihoods of their hypothetical articulatory realizations which are derived from relationships learned with aligned acoustic/articulatory data. Experiments compare this with two baseline systems, namely …...

Name ambiguity problem has raised urgent demands for efficient, high-quality named ent- ity disambiguation methods. In recent years, the increasing availability of large-scale, rich semantic knowledge sources (such as Wikipe- dia and WordNet) creates new opportunities to enhance the named entity disambiguation by developing algorithms which can exploit these knowledge …...

This paper presents a supervised approach for identifying generic noun phrases in context. Generic statements express rule- like knowledge about kinds or events. Therefore, their identification is important for the automatic construction of know- ledge bases. In particular, the distinction between generic and non-generic state- ments is crucial for the …...

We present an efficient algorithm for com- puting the weakest readings of semantically ambiguous sentences. A corpus-based eval- uation with a large-scale grammar shows that our algorithm reduces over 80% of sen- tences to one or two readings, in negligible runtime, and thus makes it possible to work with semantic …...

This paper proposes a dependency parsing method that uses bilingual constraints to improve the accuracy of parsing bilingual texts (bitexts). In our method, a target- side tree fragment that corresponds to a source-side tree fragment is identified via word alignment and mapping rules that are automatically learned. Then it is …...

In this paper we describe an intuitionistic method for dependency parsing, where a classifier is used to determine whether a pair of words forms a dependency edge. And we also propose an effective strategy for dependency projection, where the de- pendency relationships of the word pairs in the source language …...

We present algorithms for higher-order de- pendency parsing that are “third-order” in the sense that they can evaluate sub- structures containing three dependencies, and “efficient” in the sense that they re- quire only O(n4) time. Importantly, our new parsers can utilize both sibling-style and grandchild-style interactions. We evaluate our parsers …...

Letter-substitution ciphers encode a docu- ment from a known or hypothesized lan- guage into an unknown writing system or an unknown encoding of a known writing system. It is a problem that can occur in a number of practical applications, such as in the problem of determining the encod- ings …...

A central problem in historical linguistics is the identification of historically related cognate words. We present a generative phylogenetic model for automatically in- ducing cognate group structure from un- aligned word lists. Our model represents the process of transformation and trans- mission from ancestor word to daughter word, as well …...

English noun/verb (N/V) pairs (contract, cement) have undergone complex patterns of change between 3 stress patterns for several centuries. We describe a longitu- dinal dataset of N/V pair pronunciations, leading to a set of properties to be ac- counted for by any computational model. We analyze the dynamics of 5 …...

Despite its substantial coverage, Nom- Bank does not account for all within- sentence arguments and ignores extra- sentential arguments altogether. These ar- guments, which we call implicit, are im- portant to semantic processing, and their recovery could potentially benefit many NLP applications. We present a study of implicit arguments for …...

We present a natural language genera- tion approach which models, exploits, and manipulates the non-linguistic context in situated communication, using techniques from AI planning. We show how to gen- erate instructions which deliberately guide the hearer to a location that is convenient for the generation of simple referring ex- pressions, …...