README.md

metadata

license: other
task_categories:
  - sentence-similarity
language:
  - en
tags:
  - '#sentence-relatedness'
  - '#semantic-similarity'
  - '#semantic-relatedness'
pretty_name: str-2022
size_categories:
  - 1K<n<10K

STR-2022: Dataset Description

The dataset consists of 5500 English sentence pairs that are scored and ranked on a relatedness scale ranging from 0 (least related) to 1 (most related).

Loading the Dataset

• The sentence pairs, and associated scores, are in the file sem_text_rel_ranked.csv in the root directory. The CSV file can be read using:

  import pandas as pd
  
  str = pd.read_csv('sem_text_rel_ranked.csv')
  
  row = str.loc[0]
  sent1, sent2 = row['Text'].split("\n")
  score = row['Score']
  

• Relevant columns:

  • Text: Sentence pair, separated by the newline character.
  • Score: The semantic relatedness score between 0 and 1.

• Additionally:

  • the SourceID column indicates the source dataset from which the sentence pair was drawn (see Table 2 of our paper)
  • The SubsetID column indicates the sampling strategy used for the source dataset
  • and the PairID is a unique identifier for each pair that also indicates its Source and Subset.

Citing our work

Please use the following BibTex entry to cite us if you use our dataset or any of the associated analyses:

@inproceedings{abdalla2021makes,
      title={What Makes Sentences Semantically Related: A Textual Relatedness Dataset and Empirical Study},
      author={Abdalla, Mohamed and Vishnubhotla, Krishnapriya and Mohammad, Saif M.},
      year={2023},
      address = {Dubrovnik, Croatia},
      publisher = "Association for Computational Linguistics",
      booktitle = "Proceedings of the 17th Conference of the European Chapter of the Association for Computational Linguistics: Main Volume"
}

Ethics Statement

Any dataset of semantic relatedness entails several ethical considerations. We talk about this in Section 10 of our paper.

Creators

• Mohamed Abdalla (University of Toronto)
• Krishnapriya Vishnubhotla (University of Toronto)
• Saif M. Mohammad (National Research Council Canada)

Contact: msa@cs.toronto.edu, vkpriya@cs.toronto.edu, saif.mohammad@nrc-cnrc.gc.ca