Tadayoshi Hara

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The detailed analyses of sentence structure provided by parsers have been applied to address several information extraction tasks. In a recent bio-molecular event extraction task, state-of-the-art performance was achieved by systems building specifically on dependency representations of parser output. While intrinsic evaluations have shown significant(More)
The extraction of bio-molecular events from text is an important task for a number of domain applications such as pathway construction. Several syntactic parsers have been used in Biomedical Natural Language Processing (BioNLP) applications , and the BioNLP 2009 Shared Task results suggest that incorporation of syntactic analysis is important to achieving(More)
This paper describes a method of adapting a domain-independent HPSG parser to a biomedical domain. Without modifying the grammar and the probabilistic model of the original HPSG parser, we develop a log-linear model with additional features on a treebank of the biomedical domain. Since the treebank of the target domain is limited, we need to exploit an(More)
In this paper, we propose two methods for analyzing errors in parsing. One is to classify errors into categories which grammar developers can easily associate with defects in grammar or a parsing model and thus its improvement. The other is to discover inter-dependencies among errors, and thus grammar developers can focus on errors which are crucial for(More)
This paper describes an effective approach to adapting an HPSG parser trained on the Penn Treebank to a biomedical domain. In this approach, we train probabilities of lexical entry assignments to words in a target domain and then incorporate them into the original parser. Experimental results show that this method can obtain higher parsing accuracy than(More)
We present a practical HPSG parser for English, an intelligent search engine to retrieve MEDLINE abstracts that represent biomedical events and an efficient MED-LINE search tool helping users to find information about biomedical entities such as genes, proteins, and the interactions between them.
Applications using eye-tracking devices need a higher accuracy in recognition when the task reaches a certain complexity. Thus, more sophisticated methods to correct eye-tracking measurement errors are necessary to lower the penetration barrier of eye-trackers in unconstrained tasks. We propose to take advantage of the content or the structure of textual(More)
In this paper, we provide descriptive and empirical approaches to effectively extracting underlying dependencies among parsing errors. In the descriptive approach , we define some combinations of error patterns and extract them from given errors. In the empirical approach, on the other hand, we re-parse a sentence with a target error corrected and observe(More)