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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>&nbsp;</p> <p><strong>Cite</strong>&nbsp;</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&nbsp;word search query consists of a token n-gram with one&nbsp;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&nbsp;<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

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