Webis-Context-sensitive-Word-Search-Queries-2022
<pre>This is the dataset created for Language Models as Context-sensitive Word Search Engines at the In2Writing workshop at ACL22. </pre> <p> </p> <p><strong>Cite</strong> </p> <pre><code>@inproceedings{wiegmann:2022, title = "Language Models as Context-sensitive Word Search Engines", author = "Wiegmann, Matti and V{\"{o}}lske, Michael and Potthast, Martin and Stein, Benno", booktitle = "Proceedings of the 1st Workshop on Intelligent and Interactive Writing Assistants (In2Writing 2022)", month = may, year = "2022", address = "Online", publisher = "Association for Computational Linguistics",</code></pre> <p><strong>Datasets</strong></p> <p>This repository contains two datasets with word search queries. Each word search query consists of a token n-gram with one wildcard token ([MASK]). The answers to each query are the most likely token to replace the mask. All queries originate from wikitext-103 and CLOTH, the respected source is annotated for each query.</p> <p>The <em>original-token</em> dataset lists exactly one top answer for each query. The <em>ranked-answers</em> dataset lists multiple, sorted answers in three relevance categories, where 3 is the most relevant. Please refer to the citation for more details.</p>
ShareScore
36/100
Overall dataset sharing score
Score breakdown
These five areas show where the dataset supports — or may limit — practical reuse.
- Stewardship
- 8
- Harmonization
- 4
- Access
- 16
- Reuse readiness
- 8
- Engagement
- 0