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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/RRRicky-Chao/clueNERtf_bert_wwm_nlpGroup1
CLUENER2020: Fine-grained Named Entity Recognition Dataset and Benchmark for Chinese
https://github.com/Siddharthss500/zero-resource
https://github.com/Tuofengalways/ee_Model
Fast and Accurate Entity Recognition with Iterated Dilated Convolutions
https://github.com/UniversalDependencies/UD_Persian-PerDT
https://github.com/UniversalNER/uner_code
Universal NER: A Gold-Standard Multilingual Named Entity Recognition Benchmark
https://github.com/WinterShiver/Token-Path-Prediction
Reading Order Matters: Information Extraction from Visually-rich Documents by Token Path Prediction
https://github.com/Yinghao-Li/Sparse-CHMM
BERTifying the Hidden Markov Model for Multi-Source Weakly Supervised Named Entity Recognition
https://github.com/aequivinius/covid
https://github.com/aiida-/hatecrime
Reporting the Unreported: Event Extraction for Analyzing the Local Representation of Hate Crimes
https://github.com/aistairc/DeepEventMine
https://github.com/akurniawan/pytorch-sequence-tagger
https://github.com/allanj/dependency-guided-ner
https://github.com/allenai/semanticilp
Answering Complex Questions Using Open Information Extraction
https://github.com/amazon-science/tanl
Structured Prediction as Translation between Augmented Natural Languages
https://github.com/andreaskuster/ner-and-pos-when-nothing-is-capitalized
https://github.com/bodasadalla98/arabic-ner
ANER: Arabic and Arabizi Named Entity Recognition using Transformer-Based Approach
https://github.com/boy56/GDAP
Generating Disentangled Arguments with Prompts: A Simple Event Extraction Framework that Works
https://github.com/carrliitos/NLPInformationExtraction
Med7: a transferable clinical natural language processing model for electronic health records
https://github.com/centerforpeaceandsecuritystudies/icbedataset
https://github.com/changle2018/LexionAN-master
https://github.com/chaoyi-wu/pmc-llama
https://github.com/charles9n/bert-sklearn
https://github.com/chatPD-web/ChatPD
https://github.com/cipnlu/InformationExtraction
https://github.com/ckiplab/ckiptagger
Why Attention? Analyze BiLSTM Deficiency and Its Remedies in the Case of NER
https://github.com/cmdowney88/embeddingstructure
FOCUS: Effective Embedding Initialization for Monolingual Specialization of Multilingual Models
https://github.com/commitd/baleen-examples
Description of the Odin Event Extraction Framework and Rule Language
https://github.com/congyingxia/Multi-Grained-NER
https://github.com/csse-uoft/scroll
Extracting Impact Model Narratives from Social Services' Text
https://github.com/ctgatecci/Clinical-trial-eligibility-criteria-NER
Information Extraction of Clinical Trial Eligibility Criteria
https://github.com/dair-iitd/moie
https://github.com/dbmdz/historic-ner
https://github.com/derekchen14/mixture_soft_prompts
https://github.com/diffbot/knowledge-net
Entity, Relation, and Event Extraction with Contextualized Span Representations
https://github.com/edchengg/transfusion
Frustratingly Easy Label Projection for Cross-lingual Transfer
출처: Papers with Code · CC BY-SA 4.0. 아카이브 자료와 새로 수집한 논문은 별도로 관리합니다.