Data Set Used
This paper proposes a discriminative forest reranking algorithm for dependency parsing that can be seen as a form of efficient stacked parsing. A dynamic programming shift-reduce parser produces a packed derivation forest which is then scored by a discrim-inative reranker, using the 1-best tree output by the shift-reduce parser as guide features in addition… (More)
This paper reports our ongoing project for constructing an English multiword expression (MWE) dictionary and NLP tools based on the developed dictionary. We extracted functional MWEs from the English part of Wik-tionary, annotated the Penn Treebank (PTB) with MWE information, and conducted POS tagging experiments. We report how the MWE annotation is done on… (More)
This paper describes the patent translation system submitted for the NTCIR-9 PatentMT task. We applied the Linear Ordering Problem (LOP) based reordering model  to Japanese-to-English translation to deal with the substantial difference in the word order between the two languages.
This paper describes the Nara Institute of Science and Technology (NAIST) error correction system in the Helping Our Own (HOO) 2012 Shared Task. Our system targets preposition and determiner errors with spelling correction as a pre-processing step. The result shows that spelling correction improves the Detection, Correction, and Recognition F-scores for… (More)
We propose a novel unsupervised word alignment model based on the Hidden Markov Tree (HMT) model. Our model assumes that the alignment variables have a tree structure which is isomorphic to the target dependency tree and models the distortion probability based on the source dependency tree, thereby incorporating the syntactic structure from both sides of… (More)
This paper presents the NAIST dependency parser for the SANCL2012 " Parsing the Web " Shared Task. Our base system is an in-house shift-reduce parser. In order to robustly adapt the parser to heterogeneous web data, we enhanced it with (1) dependency-based clusters and (2) consensus labels from unlabeled corpora. We found that these two enhancements gave… (More)
In this paper we describe how technology can be combined with face-to-face method to facilitate teaching and learning various subjects in Tanzanian secondary schools. A smart school model is proposed. The model consists of students, teacher/facilitator/digital content expert and digital content delivery vehicles that can be implemented in a learning… (More)