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Open Information Extraction
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In natural language processing, open information extraction is the task of generating a structured, machine-readable representation of the information in text, usually in the form of triples or n-ary propositions (Source: Wikipedia).
코드
관련 논문과 평가 결과에 연결된 구현입니다. 출처에서 확인된 저자 구현에는 공식 코드 표시가 있습니다.
https://github.com/chen700564/supercd
공식 코드Few-shot Named Entity Recognition via Superposition Concept Discrimination
https://github.com/chongzhangfdu/tpp
공식 코드Reading Order Matters: Information Extraction from Visually-rich Documents by Token Path Prediction
https://github.com/cimm-kzn/RuDReC
공식 코드https://github.com/ckgconstruction/bdcp
공식 코드Robust Few-Shot Named Entity Recognition with Boundary Discrimination and Correlation Purification
https://github.com/clairebarale/refugee_cases_ner
공식 코드Automated Refugee Case Analysis: An NLP Pipeline for Supporting Legal Practitioners
https://github.com/clear-nus/edc
공식 코드Extract, Define, Canonicalize: An LLM-based Framework for Knowledge Graph Construction
https://github.com/cliang1453/BOND
공식 코드BOND: BERT-Assisted Open-Domain Named Entity Recognition with Distant Supervision
https://github.com/cocacola-lab/chatie
공식 코드ChatIE: Zero-Shot Information Extraction via Chatting with ChatGPT
https://github.com/cocacola-lab/collabkg
공식 코드https://github.com/cod3licious/conec
공식 코드Context encoders as a simple but powerful extension of word2vec
https://github.com/codermusou/nflat4cner
공식 코드NFLAT: Non-Flat-Lattice Transformer for Chinese Named Entity Recognition
https://github.com/cognitiveailab/ssa-corpus
공식 코드Extracting Space Situational Awareness Events from News Text
https://github.com/cogstack/foresight
공식 코드Foresight -- Generative Pretrained Transformer (GPT) for Modelling of Patient Timelines using EHRs
https://github.com/compnet/ddaugner
공식 코드Data Augmentation for Robust Character Detection in Fantasy Novels
https://github.com/compnet/splice
공식 코드The Role of Natural Language Processing Tasks in Automatic Literary Character Network Construction
https://github.com/conglei2xu/global-context-mechanism
공식 코드Supplementary Features of BiLSTM for Enhanced Sequence Labeling
https://github.com/contextscout/gcn_ner
공식 코드https://github.com/cooper12121/cles
공식 코드Harvesting Events from Multiple Sources: Towards a Cross-Document Event Extraction Paradigm
https://github.com/cosylabiiit/recipe-knowledge-mining
공식 코드https://github.com/cross-lingual-ner/projection-data-transfer-cross-lingual-ner
공식 코드https://github.com/csjianyang/multilingual-multimodal-nlp
공식 코드MT4CrossOIE: Multi-stage Tuning for Cross-lingual Open Information Extraction
https://github.com/cskyan/evntextrc
공식 코드Context awareness and embedding for biomedical event extraction
https://github.com/cslydia/BiFlaG
공식 코드Bipartite Flat-Graph Network for Nested Named Entity Recognition
https://github.com/cslydia/Hire-NER
공식 코드Hierarchical Contextualized Representation for Named Entity Recognition
https://github.com/csu-signal/xlingual-robustness
공식 코드Cross-Lingual Transfer Robustness to Lower-Resource Languages on Adversarial Datasets
https://github.com/cty1934/efsa
공식 코드https://github.com/cuhksz-nlp/AESINER
공식 코드Improving Named Entity Recognition with Attentive Ensemble of Syntactic Information
https://github.com/cuhksz-nlp/SANER
공식 코드Named Entity Recognition for Social Media Texts with Semantic Augmentation
https://github.com/cuishiyao96/ece
공식 코드https://github.com/d-gurgurov/Injecting-Commonsense-Knowledge-into-LLMs
공식 코드Adapting Multilingual LLMs to Low-Resource Languages with Knowledge Graphs via Adapters
https://github.com/dair-iitd/imojie
공식 코드IMoJIE: Iterative Memory-Based Joint Open Information Extraction
https://github.com/dair-iitd/mokb6
공식 코드mOKB6: A Multilingual Open Knowledge Base Completion Benchmark
https://github.com/dair-iitd/openie6
공식 코드OpenIE6: Iterative Grid Labeling and Coordination Analysis for Open Information Extraction
https://github.com/dair-iitd/zgul
공식 코드https://github.com/daixiangau/acl2020-transition-discontinuous-ner
공식 코드출처: Papers with Code · CC BY-SA 4.0. 아카이브 자료와 새로 수집한 논문은 별도로 관리합니다.