NL2FOL: Translating Natural Language to First Order Logic for Logical Fallacy Detection

Necessary packages to run the code:

Run instructions:

For converting natural language to first order logic on the given dataset: python3 nl_to_fol.py
For converting first order logic to SMT files and generate results use: python3 fol_to_cvc.py
For getting the final result metrics run: python3 get_metrics.py
To interpret the SMT results use: python3 interpret_smt_result.py <output_of_smt_file_path> <json to relevant sentence data with Claim, Implication, Referring expressions, Properties and Formula>

Name		Name	Last commit message	Last commit date
Latest commit History 64 Commits
__pycache__		__pycache__
data		data
logs		logs
prompts		prompts
results		results
README.md		README.md
combine_csvs.py		combine_csvs.py
cvc.py		cvc.py
cvc4		cvc4
dataset.csv		dataset.csv
few_shot.py		few_shot.py
few_shot_anthropic.py		few_shot_anthropic.py
few_shot_openai.py		few_shot_openai.py
fol_to_cvc.py		fol_to_cvc.py
get_metrics.py		get_metrics.py
helpers.py		helpers.py
interpret_smt_results.py		interpret_smt_results.py
nl_to_fol.py		nl_to_fol.py
parse_json_nli_dataset.py		parse_json_nli_dataset.py
run_sherlock.sh		run_sherlock.sh
run_smt_solver.py		run_smt_solver.py
setup_sherlock.sbatch		setup_sherlock.sbatch
setup_sherlock.sh		setup_sherlock.sh
test_nli_transformers.py		test_nli_transformers.py
zero_shot.py		zero_shot.py

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