EvidenceRetrieval-ClaimClassification

In this project, different methods for evidence retrieval and Claim Classification are evaluated. Specifically we used following methods:

• Vector Space
• TF-IDF
• Word Mover's Distance (WMD)
• Simple LSTM using word2vec
• Simple LSTM using ELMo
• Simple LSTM using BERT

To run classical methods such as Vector Space, TF-IDF, and WMD execute:

python -m feature_extraction.script_name

Example:

python -m feature_extraction.feature_extractor

To run deep learning methods, following steps are considered: Deep Learning Methods

How to cite

@mastersthesis{ramesh2019-defacto,
  title        = "Evidence Extraction for Fact Validation using Neural Network Architectures",
  author       = "Ramesh Kumar",
  year         = "2019",
  type         = "Master's Thesis",
  school       = "Hochschule Bonn-Rhein-Sieg"
}