GitHub topics: fact-extraction
franciellevargas/SELFAR
The SEntence-Level FActual Reasoning (SELFAR) is a new method to improve explainable fact-checking. It relies on fact extraction and verification by predicting the news source reliability and factuality (veracity) of news articles or claims at the sentence level, generating post-hoc explanations using SHAP/LIME and zero-shot prompts.
Language: Jupyter Notebook - Size: 1.14 MB - Last synced at: about 1 month ago - Pushed at: about 1 month ago - Stars: 0 - Forks: 0
IKMLab/CFEVER-data
AAAI-24 CFEVER: A Chinese Fact Extraction and VERification Dataset
Size: 1.48 MB - Last synced at: 11 months ago - Pushed at: 11 months ago - Stars: 2 - Forks: 1
twjiang/MIMO_CFE
Source code for the EMNLP 2019 paper "Multi-Input Multi-Output Sequence Labeling for Joint Extraction of Fact and Condition Tuples from Scientific Text" (给定科研文本如生物医药文献，联合抽取其中事实三元组、条件三元组，即对文献进行信息结构化)
Language: Python - Size: 206 KB - Last synced at: about 1 year ago - Pushed at: over 5 years ago - Stars: 21 - Forks: 9
Zarharan/ParsFEVER
The first dataset for Farsi fact extraction and verification
Language: JavaScript - Size: 2.16 MB - Last synced at: about 2 years ago - Pushed at: over 3 years ago - Stars: 1 - Forks: 1
