We present an elegant and extensible model that is capable of providing semantic interpretations for an unusually wide range of textual tables in documents. Unlike the few existing table analysis models, which largely...
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This article describes the generation of aggregated and elliptic sentences, using Dependency Trees connected by rhetorical relations as input. The system we have developed can generate both hypotactic and paratactic c...
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We report an experiment in which a high-performance boosting based NER model originally designed for multiple European languages is instead applied to the Chinese named entity recognition task of the third SIGHAN Chin...
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In this paper we describe a coreference resolution method that employs a classification and a clusterization phase. In a novel way, the clusterization is produced as a graph cutting algorithm, in which nodes of the gr...
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With ubiquitous computing system, users can access information through a computer network at any time and in any place. The basic infrastructure of ubiquitous computing system is wireless network environment, and a RF...
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We give an overview of the RWTH phrase-based statistical machine translation system that was used in the evaluation campaign of the International Workshop on Spoken language Translation (IWSLT) 2006. The system was ra...
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Word posterior probabilities are a common approach for confidence estimation in automatic speech recognition and machine translation. We will generalize this idea and introduce n-gram posterior probabilities and show ...
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We present discriminative reordering models for phrase-based statistical machine translation. The models are trained using the maximum entropy principle. We use several types of features: based on words, based on word...
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We present twin results on Chinese semantic parsing, with application to English-Chinese cross- lingual verb frame acquisition. First, we describe two new state-of-the-art Chinese shallow semantic parsers leading to a...
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We present twin results on Chinese semantic parsing, with application to English-Chinese cross- lingual verb frame acquisition. First, we describe two new state-of-the-art Chinese shallow semantic parsers leading to an F-score of 82.01 on simultaneous frame and argument boundary identification and labeling. Subsequently, we propose a model that applies the separate Chinese and English semantic parsers to learn cross-lingual semantic verb frame argument mappings with 89.3% accuracy. The only training data needed by this cross-lingual learning model is a pair of non-parallel monolingual Propbanks, plus an unannotated parallel corpus. We also present the first reported controlled comparison of maximum entropy and SVM approaches to shallow semantic parsing, using the Chinese data.
We present the first known direct measurement of word alignment coverage on an Arabic-English parallel corpus using inversion transduction grammar constraints. While direct measurements have been reported for several ...
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We present the first known direct measurement of word alignment coverage on an Arabic-English parallel corpus using inversion transduction grammar constraints. While direct measurements have been reported for several European and Asian languages, to date no results have been available for Arabic or any Semitic language despite much recent activity on Arabic- English spoken language and text translation. Many recent syntax based statistical MT models operate within the domain of ITG expressiveness, often for efficiency reasons, so it has become important to determine the extent to which the ITG constraint assumption holds. Our results on Arabic provide further evidence that ITG expressiveness appears largely sufficient for core MT models.
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