Papers with Code 아카이브
AMR Parsing
태스크의 하위 분류와 논문·코드·평가·기법·데이터셋을 탐색하세요.
- 하위 태스크
- 0
- 평가표
- 8
- 보존된 평가 기록
- 75
Each AMR is a single rooted, directed graph. AMRs include PropBank semantic roles, within-sentence coreference, named entities and types, modality, negation, questions, quantities, and so on. See.
코드
관련 논문과 평가 결과에 연결된 구현입니다. 출처에서 확인된 저자 구현에는 공식 코드 표시가 있습니다.
https://github.com/Cartus/DCGCN
Neural AMR: Sequence-to-Sequence Models for Parsing and Generation
https://github.com/ChunchuanLv/amr-evaluation-tool-enhanced
https://github.com/SapienzaNLP/spring
https://github.com/bjascob/amrlib
https://github.com/facebookresearch/m-amr2text
Neural AMR: Sequence-to-Sequence Models for Parsing and Generation
https://github.com/freesunshine0316/neural-graph-to-seq-mp
Neural AMR: Sequence-to-Sequence Models for Parsing and Generation
https://github.com/goodbai-nlp/amrbart
https://github.com/gotheregit/chinese-amr
https://github.com/josefigueroa168/NLP-project
https://github.com/khakhazeus/bibl
https://github.com/mdtux89/amr-eager
https://github.com/mdtux89/amr-eager-multilingual
https://github.com/pournaki/transition-amr-parser
https://github.com/sinantie/NeuralAmr
Neural AMR: Sequence-to-Sequence Models for Parsing and Generation
https://github.com/yangyucheng000/Papers/tree/main/amr2text
Neural AMR: Sequence-to-Sequence Models for Parsing and Generation
출처: Papers with Code · CC BY-SA 4.0. 아카이브 자료와 새로 수집한 논문은 별도로 관리합니다.