QED is a linguistically principled framework for explanations in question answering. Given a question and a passage, QED represents an explanation of the answer as a combination of discrete, human-interpretable steps:
sentence selection := identification of a sentence implying an answer to the question
referential equality := identification of noun phrases in the question and the answer sentence that refer to the same thing
predicate entailment := confirmation that the predicate in the sentence entails the predicate in the question once referential equalities are abstracted away.
The QED dataset is an expert-annotated dataset of QED explanations build upon a subset of the Google Natural Questions dataset.
Source: https://github.com/google-research-datasets/QED
Image Source: https://github.com/google-research-datasets/QED
Variants: QED
This dataset is used in 1 benchmark:
Task | Model | Paper | Date |
---|---|---|---|
Drug Discovery | HierG2G | Hierarchical Graph-to-Graph Translation for Molecules | 2019-06-11 |
Recent papers with results on this dataset: