• 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.

• Journal of Advanced Marine Engineering and Technology
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• v.37 no.2
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• pp.227-235
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• 2013

The quality of the part-of-speech (POS) annotation in a corpus plays an important role in developing POS taggers. There, however, are several kinds of errors in Korean POS-tagged corpora like Sejong Corpus. Such errors are likely to be various like annotation errors, spelling errors, insertion and/or deletion of unexpected characters. In this paper, we propose a method for detecting annotation errors using error patterns, and also develop a tool for effectively correcting them. Overall, based on the proposed method, we have hand-corrected annotation errors in Sejong POS Tagged Corpus using the developed tool. As the result, it is faster at least 9 times when compared without using any tools. Therefore we have observed that the proposed method is effective for correcting annotation errors in POS-tagged corpus.

• Journal of the Korea Society of Computer and Information
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• v.17 no.9
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• pp.29-38
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• 2012

In this paper, we propose a named entity and event annotation tool for cultural heritage information corpus construction. Focusing on time, location, person, and event suitable for cultural heritage information management, the annotator writes the named entities and events with the proposed tool. In order to easily annotate the named entities and the events, the proposed tool automatically annotates the location information such as the line number or the word number, and shows the corresponding string, formatted as both bold and italic, in the raw text. For the purpose of reducing the costs of the manual annotation, the proposed tool utilizes the patterns to automatically recognize the named entities. Considering the very little training corpus, the proposed tool extracts simple rule patterns. To avoid error propagation, the proposed patterns are extracted from the raw text without any additional process. Experimental results show that the proposed tool reduces more than half of the manual annotation costs.

• 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.

• Proceedings of the Korean Society for Language and Information Conference
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• 2002.02a
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• pp.1-1
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• 2002

This talk provides an overview of current work in my research group on the syntactic annotation of the T bingen corpus of spoken German and of the German Reference Corpus (Deutsches Referenzkorpus: DEREKO) of written texts. Morpho-syntactic and syntactic annotation as well as annotation of function-argument structure for these corpora is performed automatically by a hybrid architecture that combines robust symbolic parsing with finite-state methods ("chunk parsing" in the sense Abney) with memory-based parsing (in the sense of Daelemans). The resulting robust annotations can be used by theoretical linguists, who lire interested in large-scale, empirical data, and by computational linguists, who are in need of training material for a wide range of language technology applications. To aid retrieval of annotated trees from the treebank, a query tool VIQTORYA with a graphical user interface and a logic-based query language has been developed. VIQTORYA allows users to query the treebanks for linguistic structures at the word level, at the level of individual phrases, and at the clausal level.

• 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.

• Genomics & Informatics
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• v.18 no.2
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• pp.13.1-13.6
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• 2020

The prototype version of the full-text corpus of Genomics & Informatics has recently been archived in a GitHub repository. The full-text publications of volumes 10 through 17 are also directly downloadable from PubMed Central (PMC) as XML files. During the Biomedical Linked Annotation Hackathon 6 (BLAH6), we experimented with converting, annotating, and updating 301 PMC full-text articles of Genomics & Informatics using PubAnnotation, a system that provides a convenient way to add PMC publications based on PMCID. Thus, this review aims to provide a tutorial overview of practicing the iterative task of named entity recognition with the PubAnnotation/PubDictionaries/TextAE ecosystem. We also describe developing a conversion tool between the Genia tagger output and the JSON format of PubAnnotation during the hackathon.

• Annual Conference on Human and Language Technology
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• 2012.10a
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• pp.35-39
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• 2012

의미역 결정에 있어 의미 표지 부착 말뭉치는 필수적이지만 한국어 의미 표지 부착 말뭉치는 영어나 중국어와 같은 언어에 비하여 구축이 미비한 상황이다. 본 논문에서는 한국어 의미 분석을 위한 한국어 Proposition Bank(이하 PropBank)와 세종 의미 표지 부착 말뭉치의 구축을 위한 소프트웨어 도구를 개발하였다. 본 논문에서 구현한 도구는 문장 성분의 의존관계를 이용하여 주어진 술어에 대한 논항을 찾아주고, PropBank 프레임 파일과 세종 용언 격틀 사전을 활용하여 사용자가 능률적으로 한국어 PropBank와 세종 의미 표지 부착 말뭉치를 구축할 수 있도록 하였다.

• Proceedings of the Korea Information Processing Society Conference
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• 2005.05a
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• pp.741-744
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• 2005

효과적인 언어처리 시스템을 개발하기 위해서는 언어정보가 부착된 대량의 말뭉치가 필요하다. 그러나, 대량의 말뭉치를 구축하기 위해서는 많은 시간과 노력이 필요하다. 이와 같은 시간과 노력을 절약하기 위해서 일반적으로 말뭉치 구축 도구를 사용한다. 본 논문에서는 한국어 의존구조 말뭉치를 구축하기 위한 도구를 설계하고 구현하였다. 본 논문에서 개발된 구축 도구는 여러 가지 특징을 가지고 있다. 1) 특정 응용분야에 관계없이 두루 사용할 수 있다. 2) 분석 단계와 분석 오류를 연계하여 작업의 집중도를 높였다. 3) 가능한 한 오류는 축적되지 않도록 하여 구축된 말뭉치의 질을 크게 개선할 수 있었다. 4) 구축된 정보는 서로 공유할 수 있도록 하여 작업의 일관성을 극대화하였다. 5) 초보자로 사용자가 쉽게 도구를 사용할 수 있도록 인터페이스를 설계하였다. 본 논문에서 개발된 구축 도구를 이용하여 8 명의 연구원이 약 2 개월 (하루에 평균 4 시간)에 걸쳐서 10,000 문장의 의존구조 말뭉치를 구축할 수 있었다. 구축된 말뭉치에는 형태소 정보, 구묶음 정보, 의존구조 정보가 부착되어 있다.