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61
Label Verbalization and Entailment for Effective Zero and Few-Shot Relation Extraction ...
Abstract: Anthology paper link: https://aclanthology.org/2021.emnlp-main.92/ Abstract: Recent methods on prompt-based learning have shown significant performance improvements on few-shot learning. We propose a similar method for Relation Extraction by reformulating the task as Textual Entailment, achieving competitive results even in zero-shot settings. ...
Keyword: Computational Linguistics; Information Extraction; Machine Learning; Machine Learning and Data Mining; Natural Language Processing
URL: https://dx.doi.org/10.48448/sdjq-5951
https://underline.io/lecture/37744-label-verbalization-and-entailment-for-effective-zero-and-few-shot-relation-extraction
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62
Back to the Basics: A Quantitative Analysis of Statistical and Graph-Based Term Weighting Schemes for Keyword Extraction ...
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63
Separating Retention from Extraction in the Evaluation of End-to-end Relation Extraction ...
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64
XLEnt: Mining a Large Cross-lingual Entity Dataset with Lexical-Semantic-Phonetic Word Alignment ...
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65
A Data Bootstrapping Recipe for Low-Resource Multilingual Relation Classification ...
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