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NLP Expert QA Dataset
Data Science and Analytics
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About
This dataset, QASPER: NLP Questions and Evidence, is an exceptional collection of over 5,000 questions and answers focused on Natural Language Processing (NLP) papers. It has been crowdsourced from experienced NLP practitioners, with each question meticulously crafted based solely on the titles and abstracts of the respective papers. The answers provided are expertly enriched with evidence taken directly from the full text of each paper. QASPER features structured fields including 'qas' for questions and answers, 'evidence' for supporting information, paper titles, abstracts, figures and tables, and full text. This makes it a valuable resource for researchers aiming to understand how practitioners interpret NLP topics and to validate solutions for problems found in existing literature. The dataset contains 5,049 questions spanning 1,585 distinct papers.
Columns
- title: The title of the paper. (String)
- abstract: A summary of the paper. (String)
- full_text: The full text of the paper. (String)
- qas: Questions and answers about the paper. (Object)
- figures_and_tables: Figures and tables from the paper. (Object)
- id: Unique identifier for the paper.
Distribution
The QASPER dataset comprises 5,049 questions across 1,585 papers. It is distributed across five files in
.csv format, with one additional .json file for figures and tables. These include two test datasets (test.csv and validation.csv), two train datasets (train-v2-0_lessons_only_.csv and trainv2-0_unsplit.csv), and a figures dataset (figures_and_tables_.json). Each CSV file contains distinct datasets with columns dedicated to titles, abstracts, full texts, and Q&A fields, along with evidence for each paper mentioned in the respective rows.Usage
This dataset is ideal for various applications, including:
- Developing AI models to automatically generate questions and answers from paper titles and abstracts.
- Enhancing machine learning algorithms by combining answers with evidence to discover relationships between papers.
- Creating online forums for NLP practitioners, using dataset questions to spark discussion within the community.
- Conducting basic descriptive statistics or advanced predictive analytics, such as logistic regression or naive Bayes models.
- Summarising basic crosstabs between any two variables, like titles and abstracts.
- Correlating title lengths with the number of words in their corresponding abstracts to identify patterns.
- Utilising text mining technologies like topic modelling, machine learning techniques, or automated processes to summarise underlying patterns.
- Filtering terms relevant to specific research hypotheses and processing them via web crawlers, search engines, or document similarity algorithms.
Coverage
The dataset has a GLOBAL region scope. It focuses on papers within the field of Natural Language Processing. The questions and answers are crowdsourced from experienced NLP practitioners. The dataset was listed on 22/06/2025.
License
CC0
Who Can Use It
This dataset is highly suitable for:
- Researchers seeking insights into how NLP practitioners interpret complex topics.
- Those requiring effective validation for developing clear-cut solutions to problems encountered in existing NLP literature.
- NLP practitioners looking for a resource to stimulate discussions within their community.
- Data scientists and analysts interested in exploring NLP datasets through descriptive statistics or advanced predictive analytics.
- Developers and researchers working with text mining, machine learning techniques, or automated text processing.
Dataset Name Suggestions
- NLP Expert QA Dataset
- QASPER: NLP Paper Questions and Evidence
- Academic NLP Q&A Corpus
- Natural Language Processing Research Questions
Attributes
Original Data Source: QASPER: NLP Questions and Evidence
QUALITY