A Graph-based Cross-lingual Projection Approach for Weakly Supervised Relation Extraction
Code (0)
등록된 구현이 없습니다.
Tasks
RelationRelation ExtractionSimilar Papers 제목 키워드 기반
Classification-Based Self-Learning for Weakly Supervised Bilingual Lexicon Induction
Effective projection-based cross-lingual word embedding (CLWE) induction critically relies on the iterative self-learning procedure. It gradually expands the initial small seed dictionary to learn improved cross-lingual …
Bilingual Lexicon InductionClassificationGeneral ClassificationSelf-Learning+1Weakly Supervised Cross-Lingual Named Entity Recognition via Effective Annotation and Representation Projection
The state-of-the-art named entity recognition (NER) systems are supervised machine learning models that require large amounts of manually annotated data to achieve high accuracy. However, annotating NER data by human is …
Cross-Lingual NERnamed-entity-recognitionNamed Entity RecognitionNamed Entity Recognition (NER)+2Do We Really Need Fully Unsupervised Cross-Lingual Embeddings?
Recent efforts in cross-lingual word embedding (CLWE) learning have predominantly focused on fully unsupervised approaches that project monolingual embeddings into a shared cross-lingual space without any cross-lingual s…
Bilingual Lexicon InductionSelf-LearningUnsupervised Cross-Lingual Representation Learning
In this tutorial, we provide a comprehensive survey of the exciting recent work on cutting-edge weakly-supervised and unsupervised cross-lingual word representations. After providing a brief history of supervised cross-l…
Representation LearningStructured PredictionBitext Name Tagging for Cross-lingual Entity Annotation Projection
Annotation projection is a practical method to deal with the low resource problem in incident languages (IL) processing. Previous methods on annotation projection mainly relied on word alignment results without any train…
named-entity-recognitionNamed Entity RecognitionNamed Entity Recognition (NER)NER+1