5500 labeled questions & answers in training set and another 500 for test set
Dataset Description
TREC (Question Classification)
5500 labeled questions & answers in training set and another 500 for test set
Source
Huggingface Hub: link
About this dataset
The Text REtrieval Conference (TREC) Question Classification dataset contains 5500 labeled questions in training set and another 500 for test set.
The dataset has 6 coarse class labels and 50 fine class labels. Average length of each sentence is 10, vocabulary size of 8700.
Data are collected from four sources: 4,500 English questions published by USC (Hovy et al., 2001), about 500 manually constructed questions for a few rare classes, 894 TREC 8 and TREC 9 questions, and also 500 questions from TREC 10 which serves as the test set. These questions were manually labeled.
How to use the dataset
Research Ideas
- This dataset can be used to develop and test new question classification models.
- This dataset can be used to investigate the differences between human and machine question classification ability.
- This dataset can be used to study the evolution of question classification over time (e.g., changes in label usage, sentence length, etc.)
Acknowledgements
License
> License: CC0 1.0 Universal (CC0 1.0) - Public Domain Dedication
> No Copyright - You can copy, modify, distribute and perform the work, even for commercial purposes, all without asking permission. See Other Information.
Columns
File: train.csv
| Column name | Description |
|---|---|
| label-coarse | The coarse-grained label for the question. (String) |
| label-fine | The fine-grained label for the question. (String) |
| text | The text of the question. (String) |
File: test.csv
| Column name | Description |
|---|---|
| label-coarse | The coarse-grained label for the question. (String) |
| label-fine | The fine-grained label for the question. (String) |
| text | The text of the question. (String) |
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