Philip Arthur

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This paper describes the Nara Institute of Science and Tech-nology's system for the entrance exam pilot task of CLEF 2013 QA4MRE. The core of the system is a similar to the system for the main task of CLEF 2013 QA4MRE. We use minimum error rate training (MERT) to train the weights of the model and also propose a novel method for MERT with the addition of a(More)
Neural machine translation (NMT) often makes mistakes in translating low-frequency content words that are essential to understanding the meaning of the sentence. We propose a method to alleviate this problem by augmenting NMT systems with discrete translation lexicons that efficiently encode translations of these low-frequency words. We describe a method to(More)
This paper describes the Nara Institute of Science and Tech-nology's system for the main task of CLEF 2013 QA4MRE. The core of the system is a log linear scoring model that couples both intra and inter-sentence features. Each of the features receives an input of a candidate answer, question, and document, and uses these to assign a score according to some(More)
We propose a method for simultaneously translating from a single source language to multiple target languages T1, T2, etc. The motivation behind this method is that if we only have a weak language model for T1 and translations in T1 and T2 are associated, we can use the information from a strong language model over T2 to disambiguate the translations in T1,(More)
We propose a new method for semantic parsing of ambiguous and ungrammatical input, such as search queries. We do so by building on an existing semantic parsing framework that uses synchronous context free grammars (SCFG) to jointly model the input sentence and output meaning representation. We generalize this SCFG framework to allow not one, but multiple(More)
This paper describes the design of question answering system that participates in the maintask of QA4MRE at CLEF 2013. This system will initially perform preprocessing stage of the document and the documents related questions. Then, it identifies the type of questions in order to be able to search the answers with the most appropriate approach. In order to(More)
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