환유 연구를 위한 말뭉치의 구축과 주석 -신문 말뭉치에 나타난 도시명의 환유 주석을 중심으로-
Building and Annotating Corpus for Metonymy Research
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In this study, we built an annotated corpus of city names and analyzed it for types of metonymy. We laid out guidelines for the metonymy analysis and calculated the interrater reliability using the metonymy-tagged corpus. To build a raw corpus, we selected three newspapers (Chosun, Joongang, and Hangyeore) and collected news articles from 6 days of each month from January 2018 to November 2019 (total 23 months) using the Big Kinds service. The total size of the raw corpus is about 7.4 million words. Then, we annotated the raw corpus using the Open API service of the Electronics and Telecommunications Research Institute (ETRI) and built a POS-tagged and Named-Entity-tagged corpus. We converted the annotated corpus into the input format of the “Malsseum 2017” Concordancer and generated KWIC data of city and capital names. On the KWIC data, we added annotations of major types and subtypes of metonymy and calculated the interrater reliability. Because different methods of calculating interrater reliability emphasize slightly different parameters, we adopted the two most commonly used methods – Cohen’s Kappa coefficient and Krippendorff’s Alpha coefficient. We confirmed that these two methods yield almost identical coefficient scores above 0.7, which indicates strong reliability between the two raters. Throughout this entire process, we verified that our method of building an annotated corpus of city names and our guidelines for metonymy annotation are consistent and reliable. In this way, we assure that the metonymy-annotated corpus of city names is of high enough quality to be used in future related research.
Abstract
In this study, we built an annotated corpus of city names and analyzed it for types of metonymy. We laid out guidelines for the metonymy analysis and calculated the interrater reliability using the metonymy-tagged corpus. To build a raw corpus, we selected three newspapers (Chosun, Joongang, and Hangyeore) and collected news articles from 6 days of each month from January 2018 to November 2019 (total 23 months) using the Big Kinds service. The total size of the raw corpus is about 7.4 million words. Then, we annotated the raw corpus using the Open API service of the Electronics and Telecommunications Research Institute (ETRI) and built a POS-tagged and Named-Entity-tagged corpus. We converted the annotated corpus into the input format of the “Malsseum 2017” Concordancer and generated KWIC data of city and capital names. On the KWIC data, we added annotations of major types and subtypes of metonymy and calculated the interrater reliability. Because different methods of calculating interrater reliability emphasize slightly different parameters, we adopted the two most commonly used methods – Cohen’s Kappa coefficient and Krippendorff’s Alpha coefficient. We confirmed that these two methods yield almost identical coefficient scores above 0.7, which indicates strong reliability between the two raters. Throughout this entire process, we verified that our method of building an annotated corpus of city names and our guidelines for metonymy annotation are consistent and reliable. In this way, we assure that the metonymy-annotated corpus of city names is of high enough quality to be used in future related research.
참고문헌 (33)
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