|
--- |
|
dataset_info: |
|
features: |
|
- name: sentence1 |
|
dtype: string |
|
- name: sentence2 |
|
dtype: string |
|
- name: gold_label |
|
dtype: string |
|
- name: genre |
|
dtype: string |
|
splits: |
|
- name: train |
|
num_bytes: 532705 |
|
num_examples: 4068 |
|
download_size: 146614 |
|
dataset_size: 532705 |
|
configs: |
|
- config_name: default |
|
data_files: |
|
- split: train |
|
path: data/train-* |
|
license: cc-by-sa-4.0 |
|
task_categories: |
|
- text-classification |
|
language: |
|
- en |
|
--- |
|
# Dataset Card for "med" |
|
|
|
Crowsourced (=original part) of the MED dataset for Monotonicity Entailment |
|
https://github.com/verypluming/MED |
|
``` |
|
@inproceedings{yanaka-etal-2019-neural, |
|
title = "Can Neural Networks Understand Monotonicity Reasoning?", |
|
author = "Yanaka, Hitomi and |
|
Mineshima, Koji and |
|
Bekki, Daisuke and |
|
Inui, Kentaro and |
|
Sekine, Satoshi and |
|
Abzianidze, Lasha and |
|
Bos, Johan", |
|
booktitle = "Proceedings of the 2019 ACL Workshop BlackboxNLP: Analyzing and Interpreting Neural Networks for NLP", |
|
year = "2019", |
|
pages = "31--40", |
|
} |
|
``` |