Articles

In this paper, we present a method that improves Japanese dependency parsing by using large-scale statistical information. It takes into account two kinds of informa- tion not considered in previous statistical (machine learning based) parsing meth- ods: information about dependency rela- tions among the case elements of a verb, and …...

This paper proposes a novel composite ker- nel for relation extraction. The composite kernel consists of two individual kernels: an entity kernel that allows for entity-related features and a convolution parse tree kernel that models syntactic information of relation examples. The motivation of our method is to fully utilize the …...

In a new approach to large-scale extrac- tion of facts from unstructured text, dis- tributional similarities become an integral part of both the iterative acquisition of high-coverage contextual extraction pat- terns, and the validation and ranking of candidate facts. The evaluation mea- sures the quality and coverage of facts extracted …...

We propose a novel algorithm for inducing seman- tic taxonomies. Previous algorithms for taxonomy induction have typically focused on independent classifiers for discovering new single relationships based on hand-constructed or automatically discov- ered textual patterns. By contrast, our algorithm flexibly incorporates evidence from multiple clas- sifiers over heterogenous relationships to …...

Many algorithms have been developed to harvest lexical semantic resources, however few have linked the mined knowledge into formal knowledge re- positories. In this paper, we propose two algorithms for automatically ontologiz- ing (attaching) semantic relations into WordNet. We present an empirical evaluation on the task of attaching part- of …...

We present a hierarchical phrase-based statistical machine translation in which a target sentence is efficiently generated in left-to-right order. The model is a class of synchronous-CFG with a Greibach Nor- mal Form-like structure for the projected production rule: The paired target-side of a production rule takes a phrase pre- fixed …...

In the past years, a number of lexical association measures have been studied to help extract new scientific terminol- ogy or general-language collocations. The implicit assumption of this research was that newly designed term measures involv- ing more sophisticated statistical criteria would outperform simple counts of co- occurrence frequencies. We …...

Named Entity recognition (NER) is an important part of many natural language processing tasks. Current approaches of- ten employ machine learning techniques and require supervised data. However, many languages lack such resources. This paper presents an (almost) unsupervised learning algorithm for automatic discov- ery of Named Entities (NEs) in a …...

We introduce a semi-supervised approach to training for statistical machine transla- tion that alternates the traditional Expecta- tion Maximization step that is applied on a large training corpus with a discriminative step aimed at increasing word-alignment quality on a small, manually word-aligned sub-corpus. We show that our algorithm leads not …...

We present a perceptron-style discriminative ap- proach to machine translation in which large feature sets can be exploited. Unlike discriminative rerank- ing approaches, our system can take advantage of learned features in all stages of decoding. We first discuss several challenges to error-driven discrim- inative approaches. In particular, we explore …...

This paper investigates a machine learn- ing approach for temporally ordering and anchoring events in natural language texts. To address data sparseness, we used temporal reasoning as an over- sampling method to dramatically expand the amount of training data, resulting in predictive accuracy on link labeling as high as 93% …...

The paper presents a new model for context- dependent interpretation of linguistic expressions about spatial proximity between objects in a nat- ural scene. The paper discusses novel psycholin- guistic experimental data that tests and verifies the model. The model has been implemented, and en- ables a conversational robot to identify …...

This paper presents a novel training al- gorithm for a linearly-scored block se- quence translation model. The key com- ponent is a new procedure to directly op- timize the global scoring function used by a SMT decoder. No translation, language, or distortion model probabilities are used as in earlier work …...

Call centers handle customer queries from various domains such as computer sales and support, mo- bile phones, car rental, etc. Each such domain generally has a domain model which is essential to handle customer complaints. These models contain common problem categories, typical cus- tomer issues and their solutions, greeting styles. …...

The noisy channel model approach is suc- cessfully applied to various natural lan- guage processing tasks. Currently the main research focus of this approach is adaptation methods, how to capture char- acteristics of words and expressions in a target domain given example sentences in that domain. As a solution we …...

In this paper, we present a novel global re- ordering model that can be incorporated into standard phrase-based statistical ma- chine translation. Unlike previous local reordering models that emphasize the re- ordering of adjacent phrase pairs (Till- mann and Zhang, 2005), our model ex- plicitly models the reordering of long …...

In this paper, we present a method for guessing POS tags of unknown words us- ing local and global information. Al- though many existing methods use only local information (i.e. limited window size or intra-sentential features), global in- formation (extra-sentential features) pro- vides valuable clues for predicting POS tags of …...

With performance above 97% accuracy for newspaper text, part of speech (POS) tag- ging might be considered a solved prob- lem. Previous studies have shown that allowing the parser to resolve POS tag ambiguity does not improve performance. However, for grammar formalisms which use more fine-grained grammatical cate- gories, for …...

We present a method for Noun Phrase chunking in Hebrew. We show that the traditional definition of base-NPs as non- recursive noun phrases does not apply in Hebrew, and propose an alternative defi- nition of Simple NPs. We review syntac- tic properties of Hebrew related to noun phrases, which indicate …...

We present MAGEAD, a morphological analyzer and generator for the Arabic lan- guage family. Our work is novel in that it explicitly addresses the need for pro- cessing the morphology of the dialects. MAGEAD performs an on-line analysis to or generation from a root+pattern+features representation, it has separate phonologi- cal …...