태스크의 하위 분류와 논문·코드·평가·기법·데이터셋을 탐색하세요.
Dialog Relation Extraction is the task of predicting the relation type between entities mentioned in dialogue. It uses multiple tokens to capture possible relations between pairs of entities in the dialogue. The popular benchmark for this task is the DialogRE dataset. The models are typically evaluated with the metric of F1 Score for both standard-setting and conversational settings.
출처에 같은 태스크 이름으로 연결된 데이터셋입니다. 동명 태스크가 포함될 수 있으므로, 비교할 때는 평가 결과의 조건도 확인하세요.
DialogRE is the first human-annotated dialogue-based relation extraction dataset, containing 1,788 dialogues originating from the complete transcripts of a famous American television situation comedy Friends. The are annotations for all occurrences of 36 possible relation types that exist between an argument pair in a dialogue. DialogRE is available in English and Chinese. Source: DialogRE
DDRel is a dataset for interpersonal relation classification in dyadic dialogues. It consists of 6,300 dyadic dialogue sessions between 694 pairs of speakers with 53,126 utterances in total. It is constructed by crawling movie scripts from IMSDb and annotating the relation labels for each session according to 13 pre-defines relationships. Source: https://github.com/JiaQiSJTU/DialogueRelationClassification
출처: Papers with Code · CC BY-SA 4.0. 아카이브 자료와 새로 수집한 논문은 별도로 관리합니다.