question-score 0.0.0

library for question evaluation including KDA, Knowledge Dependent Answerability introduced in EMNLP 2022 work.

question-score

Repository for KDA(Knowledge-dependent Answerability), EMNLP 2022 work

How to use

pip install -e .

from question_score import KDA
kda = KDA()
print(
  kda.kda_small(
    "passage",
    "question",
    ["option1", "option2", "option3", "option4"],
    1
  )
)

What does the score mean?

You can check the explanation of KDA on https://arxiv.org/abs/2211.11902 now. The official link from EMNLP 2022 will soon be released.

You can use $KDA_{small}$ or $KDA_{large}$ instead of heavy metric using all model. Below is the performance of the submetrics, which mentioned on the appendix of the paper.

Sub Metric	Model Count ( Total Size )	KDA (Valid)	Likert (Test)
KDA_small	4 (3.5GB)	0.740	0.377
KDA_large	10 (19.2GB)	0.784	0.421

Citation

@inproceedings{moon2022eval,
  title={Evaluating the Knowledge Dependency of Questions,
  author={Moon, H., Yang, Y., Shin, J., Yu, H., Lee, S., Jeong, M., Park, J., Kim, M., & Choi, S.},
  booktitle={Proceedings of the 2022 Conference on Empirical Methods in Natural Language Processing},
  year={2022}
}