Papers with Code 아카이브

Document-level Event Extraction

태스크의 하위 분류와 논문·코드·평가·기법·데이터셋을 탐색하세요.

하위 태스크
0
평가표
1
보존된 평가 기록
4

데이터셋

출처에 같은 태스크 이름으로 연결된 데이터셋입니다. 동명 태스크가 포함될 수 있으므로, 비교할 때는 평가 결과의 조건도 확인하세요.

ChFinAnn

Ten years (2008-2018) ChFinAnn documents and human-summarized event knowledge bases to conduct the DS-based event labeling. Five event types included: Equity Freeze (EF), Equity Repurchase (ER), Equity Underweight (EU), Equity Overweight (EO) and Equity Pledge (EP), which belong to major events required to be disclosed by the regulator and may have a huge impact on the company value. To ensure the labeling quality, the authors set constraints for matched document-record pairs. There are 32, 040 documents in total, and this number is ten times larger than 2, 976 of DCFEE and about 53 times larger than 599 of ACE 2005. These documents are divided into train, development, and test set with the proportion of 8 : 1 : 1 based on the time order. This DS-generated data are pretty good, achieving high precision and acceptable recall. In later experiments, the authors directly employ the automatically generated test set for evaluation due to its much broad coverage.

LEMONADE

LEMONADE is a large, expert-annotated dataset for event extraction from news articles in 20 languages: English, Spanish, Arabic, French, Italian, Russian, German, Turkish, Burmese, Indonesian, Ukrainian, Korean, Portuguese, Dutch, Somali, Nepali, Chinese, Persian, Hebrew, and Japanese.

출처: Papers with Code · CC BY-SA 4.0. 아카이브 자료와 새로 수집한 논문은 별도로 관리합니다.