https://github.com/pefimov/cross-lingual-adjustment
공식 코드The Impact of Cross-Lingual Adjustment of Contextual Word Representations on Zero-Shot Transfer
Papers with Code 아카이브
Open Information Extraction
태스크의 하위 분류와 논문·코드·평가·기법·데이터셋을 탐색하세요.
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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/pfliu-nlp/Named-Entity-Recognition-NER-Papers
공식 코드Rethinking Generalization of Neural Models: A Named Entity Recognition Case Study
https://github.com/phenixace/MFE-NER
공식 코드MFE-NER: Multi-feature Fusion Embedding for Chinese Named Entity Recognition
https://github.com/phongnt570/large-scale-csk-extraction
공식 코드https://github.com/pinkeshbadjatiya/twitter-hatespeech
공식 코드https://github.com/pkunlp-icler/censor
공식 코드https://github.com/pkunlp-icler/scl-rai
공식 코드https://github.com/pkunlp-icler/tsar
공식 코드A Two-Stream AMR-enhanced Model for Document-level Event Argument Extraction
https://github.com/pluslabnlp/clap
공식 코드Contextual Label Projection for Cross-Lingual Structured Prediction
https://github.com/pluslabnlp/degree
공식 코드DEGREE: A Data-Efficient Generation-Based Event Extraction Model
https://github.com/qijimrc/robust
공식 코드Preserving Knowledge Invariance: Rethinking Robustness Evaluation of Open Information Extraction
https://github.com/qijimrc/robustoie
공식 코드Syntactically Robust Training on Partially-Observed Data for Open Information Extraction
https://github.com/qingyu-qc/bioner_gerbera
공식 코드Augmenting Biomedical Named Entity Recognition with General-domain Resources
https://github.com/qiuhaolu/tner
공식 코드Large Language Models Struggle in Token-Level Clinical Named Entity Recognition
https://github.com/qznan/spankl
공식 코드A Neural Span-Based Continual Named Entity Recognition Model
https://github.com/rahulpatchigolla/EventTriggerDetection
공식 코드Biomedical Event Trigger Identification Using Bidirectional Recurrent Neural Network Based Models
https://github.com/raja-kumar/knowledge-grounded-tods
공식 코드Task Oriented Conversational Modelling With Subjective Knowledge
https://github.com/rali-udem/WiRe57
공식 코드WiRe57 : A Fine-Grained Benchmark for Open Information Extraction
https://github.com/ramisa2108/bangla-complex-named-entity-recognition-challenge
공식 코드BanglaCoNER: Towards Robust Bangla Complex Named Entity Recognition
https://github.com/randyzhouran/conner
공식 코드ConNER: Consistency Training for Cross-lingual Named Entity Recognition
https://github.com/randyzhouran/melm
공식 코드MELM: Data Augmentation with Masked Entity Language Modeling for Low-Resource NER
https://github.com/raotnameh/End-to-end-E2E-Named-Entity-Recognition-from-English-Speech
공식 코드https://github.com/raspberryice/gen-arg
공식 코드Document-Level Event Argument Extraction by Conditional Generation
https://github.com/raspberryice/type-discovery-abs
공식 코드Open Relation and Event Type Discovery with Type Abstraction
https://github.com/ratmcu/wikipiifed
공식 코드https://github.com/realsarm/reportql
공식 코드https://github.com/rendanim/mphayaner
공식 코드https://github.com/revdotcom/speech-datasets/tree/main/earnings21
공식 코드https://github.com/richielee93/eder
공식 코드EDeR: A Dataset for Exploring Dependency Relations Between Events
https://github.com/ringbdstack/gdap
공식 코드Generating Disentangled Arguments with Prompts: A Simple Event Extraction Framework that Works
https://github.com/ritual-uh/style_ner
공식 코드https://github.com/ritwikmishra/indicgenqa
공식 코드Long-context Non-factoid Question Answering in Indic Languages
https://github.com/rsabilio/nereval-braziliancorporatetranscriptions
공식 코드https://github.com/rsabilio/nereval-braziliancorporatetranscripts
공식 코드https://github.com/rtmaww/x-piece
공식 코드Searching for Optimal Subword Tokenization in Cross-domain NER
https://github.com/rttl-ai/bioptimus
공식 코드출처: Papers with Code · CC BY-SA 4.0. 아카이브 자료와 새로 수집한 논문은 별도로 관리합니다.