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

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

• Language and Information
• /
• v.6 no.1
• /
• pp.123-138
• /
• 2002

This paper discusses issues in building a 54-thousand-word Korean Treebank using a phrase structure annotation, along with developing annotation guidelines based on the morpho-syntactic phenomena represented in the corpus. Various methods that were employed for quality control are presented. The evaluation on the quality of the Treebank and some of the NLP applications under development using the Treebank are also pre-sented.

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

• Genomics & Informatics
• /
• v.19 no.3
• /
• pp.23.1-23.7
• /
• 2021

Currently, coronavirus disease 2019 (COVID-19) literature has been increasing dramatically, and the increased text amount make it possible to perform large scale text mining and knowledge discovery. Therefore, curation of these texts becomes a crucial issue for Bio-medical Natural Language Processing (BioNLP) community, so as to retrieve the important information about the mechanism of COVID-19. PubAnnotation is an aligned annotation system which provides an efficient platform for biological curators to upload their annotations or merge other external annotations. Inspired by the integration among multiple useful COVID-19 annotations, we merged three annotations resources to LitCovid data set, and constructed a cross-annotated corpus, LitCovid-AGAC. This corpus consists of 12 labels including Mutation, Species, Gene, Disease from PubTator, GO, CHEBI from OGER, Var, MPA, CPA, NegReg, PosReg, Reg from AGAC, upon 50,018 COVID-19 abstracts in LitCovid. Contain sufficient abundant information being possible to unveil the hidden knowledge in the pathological mechanism of COVID-19.

• Journal of Computing Science and Engineering
• /
• v.2 no.2
• /
• pp.162-179
• /
• 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
• /
• v.13B no.1 s.104
• /
• pp.63-70
• /
• 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
• /
• 2002.02a
• /
• pp.1-1
• /
• 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.

• Language and Information
• /
• v.17 no.2
• /
• pp.67-91
• /
• 2013

This paper describes Korean Nominal Bank, a project that provides argument structure for instances of the predicative nouns in the Sejong parsed Corpus. We use the language resources of the Sejong project, so that the same set of data is annotated with more and more levels of annotation, since a new type of a language resource building project could bring new information of separate and isolated processing. We have based on the annotation scheme based on the Sejong electronic dictionary, semantically tagged corpus, and syntactically analyzed corpus. Our work also involves the deep linguistic knowledge of syntaxsemantic interface in general. We consider the semantic theories including the Frame Semantics of Fillmore (1976), argument structure of Grimshaw (1990) and argument alternation of Levin (1993), and Levin and Rappaport Hovav (2005). Various syntactic theories should be needed in explaining various sentence types, including empty categories, raising, left (or right dislocation). We also need an explanation on the idiosyncratic lexical feature, such as collocation and etc.

• Proceedings of the KSPS conference
• /
• 2002.11a
• /
• pp.27-32
• /
• 2002

In this paper it is discussed what should be taken into consideration with respect to segmentation and labeling in creation of speech corpus. What levels of annotation and what kind of contents should be included, what kind of acoustic information is checked for in segmentation, etc are discussed.