119 datasets found

The dataset used in the paper is the TREC dataset, which consists of 124 queries.

The CGQA dataset is a large dataset containing 413 attributes and 674 object categories.

The SQuAD dataset is a benchmark for natural language understanding tasks, including question answering and text classification.

FarFetched is a modular framework that enables people to verify any kind of textual claim based on the incorporated evidence from textual news sources.

The dataset used in the paper is a collection of irrelevant questions that are more challenging than the ones in existing datasets.

The bAbI Question Answering dataset is a benchmark for evaluating the ability of RNNs to answer questions.

A dataset of NSMQ contests from 2012-2022 containing videos of the contest and corresponding metadata, text form of riddles questions, and open-source science textbooks.

The task of Question Answering over Linked Data (QALD) has received increased attention over the last years (see the surveys [14] and [36]). The task consists in mapping natural...

The InsuranceQA dataset is a question answering dataset containing questions and answers.

The conversational dataset is used to evaluate the performance of the proposed algorithms. The dataset consists of 20,000 questions and answers, where each question is answered...

The dataset used in the paper is a corpus of text containing approximately 10,000 examples, each a sequence of sentences extracted from books.

EuSQuAD: Automatically Translated and Aligned SQuAD2.0 for Basque

The TruthfulQA dataset is a dataset that contains 817 questions designed to evaluate language models' preference to mimic some human falsehoods.

The BioASQ dataset contains questions and answers from various sources, including Wikipedia and biomedical literature.

The dataset used in the paper is the SNLI dataset.

DEFT consists of two categories of definitions: a) Contracts: involving 2,433 sentences from the 2017 SEC contract filing, and b) Textbook: involving 21,303 sentences from...

FVQA is a fact-based visual question answering dataset, containing 2190 images and 5826 (question, answer) pairs, with supporting facts selected from knowledge bases.

Clinical text structuring is a critical and fundamental task for clinical research. Traditional methods such as task-specific end-to-end models and pipeline models usually...

A usable library for question answering on large datasets

The QQP dataset contains more than 400k question pairs.