• Proceedings of the Korean Society for Language and Information Conference
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• 2007.11a
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• pp.385-393
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• 2007

Corpora annotated with lots of linguistic information are required to develop robust and statistical natural language processing systems. Building such corpora, however, is an expensive, labor-intensive, and time-consuming work. To help the work, we design and implement an annotation tool for establishing a Korean dependency tree-tagged corpus. Compared with other annotation tools, our tool is characterized by the following features: independence of applications, localization of errors, powerful error checking, instant annotated information sharing, user-friendly. Using our tool, we have annotated 100,904 Korean sentences with dependency structures. The number of annotators is 33, the average annotation time is about 4 minutes per sentence, and the total period of the annotation is 5 months. We are confident that we can have accurate and consistent annotations as well as reduced labor and time.

• Genomics & Informatics
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• v.18 no.2
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• pp.18.1-18.5
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• 2020

Finding publications that propose alternative methods to animal experiments is an important but time-consuming task since researchers need to perform various queries to literature databases and screen many articles to assess two important aspects: the relevance of the article to the research question, and whether the article's proposed approach qualifies to being an alternative method. We are currently developing a Web application to support finding alternative methods to animal experiments. The current (under development) version of the application utilizes external tools and resources for document processing, and relies on the PubAnnotation ecosystem for annotation querying, annotation storage, dictionary-based tagging of cell lines, and annotation visualization. Currently, our two PubAnnotation repositories for discourse elements contain annotations for more than 110k PubMed documents. Further, we created an annotator for cell lines that contain more than 196k terms from Cellosaurus. Finally, we are experimenting with TextAE for annotation visualization and for user feedback.

• Journal of Computing Science and Engineering
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• v.2 no.2
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• pp.162-179
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• 2008

We have developed a tool for annotation of electronic health record (EHR) data. Currently we are in the process of manually annotating a corpus of Norwegian general practitioners' EHRs with mainly linguistic information. The purpose of this project is to attain a linguistically annotated corpus of patient histories from general practice. This corpus will be put to future use in medical language processing and information extraction applications. The paper outlines some of our practical experiences from developing such a corpus and, in particular, the effects of semi-automated annotation. We have also done some preliminary experiments with part-of-speech tagging based on our corpus. The results indicated that relevant training data from the clinical domain gives better results for the tagging task in this domain than training the tagger on a corpus form a more general domain. We are planning to expand the corpus annotations with medical information at a later stage.

• The KIPS Transactions:PartB
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• v.13B no.1 s.104
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• pp.63-70
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• 2006

In general, a corpus contains lots of linguistic information and is widely used in the field of natural language processing and computational linguistics. The creation of such the corpus, however, is an expensive, labor-intensive and time-consuming work. To alleviate this problem, annotation tools to build corpora with much linguistic information is indispensable. In this paper, we design and implement an annotation tool for establishing a Korean dependency tree-tagged corpus. The most ideal way is to fully automatically create the corpus without annotators' interventions, but as a matter of fact, it is impossible. The proposed tool is semi-automatic like most other annotation tools and is designed to edit errors, which are generated by basic analyzers like part-of-speech tagger and (partial) parser. We also design it to avoid repetitive works while editing the errors and to use it easily and friendly. Using the proposed annotation tool, 10,000 Korean sentences containing over 20 words are annotated with dependency structures. For 2 months, eight annotators have worked every 4 hours a day. We are confident that we can have accurate and consistent annotations as well as reduced labor and time.