Fact Checking

🚀 Fact checking

This generative model, trained on FEVER, is designed to predict whether a claim aligns with the provided evidence.

🚀 Quick Start

📦 Installation

One quick way to install it is to type:

pip install fact_checking

💻 Usage Examples

Basic Usage

After installation, you can use the following code:

from transformers import (
    GPT2LMHeadModel,
    GPT2Tokenizer,
)

from fact_checking import FactChecker

_evidence = """
Justine Tanya Bateman (born February 19, 1966) is an American writer, producer, and actress . She is best known for her regular role as Mallory Keaton on the sitcom Family Ties (1982 -- 1989). Until recently, Bateman ran a production and consulting company, SECTION 5 . In the fall of 2012, she started studying computer science at UCLA.
"""

_claim = 'Justine Bateman is a poet.'

tokenizer = GPT2Tokenizer.from_pretrained('gpt2')
fact_checking_model = GPT2LMHeadModel.from_pretrained('fractalego/fact-checking')
fact_checker = FactChecker(fact_checking_model, tokenizer)
is_claim_true = fact_checker.validate(_evidence, _claim)

print(is_claim_true)

The output of the above code will be:

False

Advanced Usage

The output can include a probabilistic component, obtained by iterating a number of times the output generation. The system generates an ensemble of answers and groups them by Yes or No.

For example:

from transformers import (
    GPT2LMHeadModel,
    GPT2Tokenizer,
)

from fact_checking import FactChecker

_evidence = """
Jane writes code for Huggingface.
"""

_claim = 'Jane is an engineer.'


tokenizer = GPT2Tokenizer.from_pretrained('gpt2')
fact_checking_model = GPT2LMHeadModel.from_pretrained('fractalego/fact-checking')
fact_checker = FactChecker(fact_checking_model, tokenizer)
is_claim_true = fact_checker.validate_with_replicas(_evidence, _claim)

print(is_claim_true)

The output will be:

{'Y': 0.95, 'N': 0.05}

📚 Documentation

Score on FEVER

The predictions are evaluated on a subset of the FEVER dev dataset, restricted to the SUPPORTING and REFUTING options:

⚠️ Important Note

These results should be taken with many grains of salt. This is still a work in progress, and there might be leakage coming from the underlining GPT2 model unnaturally raising the scores.