Papers with Code 아카이브
Semantic Role Labeling
태스크의 하위 분류와 논문·코드·평가·기법·데이터셋을 탐색하세요.
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- 보존된 평가 기록
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Semantic role labeling aims to model the predicate-argument structure of a sentence and is often described as answering "Who did what to whom". BIO notation is typically used for semantic role labeling.
Example:
| Housing | starts | are | expected | to | quicken | a | bit | from | August’s | pace |
|---|---|---|---|---|---|---|---|---|---|---|
| B-ARG1 | I-ARG1 | O | O | O | V | B-ARG2 | I-ARG2 | B-ARG3 | I-ARG3 | I-ARG3 |
코드
관련 논문과 평가 결과에 연결된 구현입니다. 출처에서 확인된 저자 구현에는 공식 코드 표시가 있습니다.
https://github.com/kervyRivas/Graph-convolutional-
Encoding Sentences with Graph Convolutional Networks for Semantic Role Labeling
https://github.com/kinimod23/NMT_Project
https://github.com/kunde122/bilm-tf
https://github.com/leduoyang/IRIE_project_2018_relation_extraction
Textual Analogy Parsing: What's Shared and What's Compared among Analogous Facts
https://github.com/linghduoduo/NLP
https://github.com/luheng/deep_srl
https://github.com/maexe/linspector-web
LINSPECTOR: Multilingual Probing Tasks for Word Representations
https://github.com/mdtux89/amr-eager
https://github.com/mdtux89/amr-eager-multilingual
https://github.com/menajosep/AleatoricSent
https://github.com/mingdachen/bilm-tf
https://github.com/nafitzgerald/nrl-qasrl
https://github.com/nlp-research/bilm-tf
https://github.com/orensul/analogies_mining
https://github.com/orensultan/AIRecolor
https://github.com/riccorl/transformer-srl
Simple BERT Models for Relation Extraction and Semantic Role Labeling
https://github.com/richinkabra/CoVe-BCN
https://github.com/s-gupta/v-coco
https://github.com/sarveshsparab/DeepElmoEmbedNer
https://github.com/scofield7419/hesyfu
https://github.com/seunghwan1228/ELMO
https://github.com/shaneding/bilm-tf-experimentation
https://github.com/shelleyHLX/bilm_EMLo
https://github.com/shishir-roy/decaNLP-with-BERT
The Natural Language Decathlon: Multitask Learning as Question Answering
https://github.com/sigtyp/ST2024
The Natural Language Decathlon: Multitask Learning as Question Answering
https://github.com/stanford-oval/genienlp
The Natural Language Decathlon: Multitask Learning as Question Answering
https://github.com/synlp/srl-mm
https://github.com/turbo-llm/turbo-alignment
AllenNLP: A Deep Semantic Natural Language Processing Platform
https://github.com/uclanlp/Fast-and-Robust-Text-Classification
Men Also Like Shopping: Reducing Gender Bias Amplification using Corpus-level Constraints
https://github.com/weixsong/bilm-tf
https://github.com/yangrui123/Hidden
https://github.com/yangzonglin1994/bilm-tf-extended
https://github.com/young-zonglin/bilm-tf-extended
https://github.com/yuanjing-zhu/elmo
https://github.com/yuanxiaosc/ELMo
출처: Papers with Code · CC BY-SA 4.0. 아카이브 자료와 새로 수집한 논문은 별도로 관리합니다.