Librarian Bot: Add language metadata for dataset
Browse filesThis pull request aims to enrich the metadata of your dataset by adding language metadata to `YAML` block of your dataset card `README.md`.
How did we find this information?
- The librarian-bot downloaded a sample of rows from your dataset using the [dataset-server](https://huggingface.co/docs/datasets-server/) library
- The librarian-bot used a language detection model to predict the likely language of your dataset. This was done on columns likely to contain text data.
- Predictions for rows are aggregated by language and a filter is applied to remove languages which are very infrequently predicted
- A confidence threshold is applied to remove languages which are not confidently predicted
The following languages were detected with the following mean probabilities:
- English (en): 97.09%
If this PR is merged, the language metadata will be added to your dataset card. This will allow users to filter datasets by language on the [Hub](https://huggingface.co/datasets).
If the language metadata is incorrect, please feel free to close this PR.
To merge this PR, you can use the merge button below the PR:
This PR comes courtesy of [Librarian Bot](https://huggingface.co/librarian-bots). If you have any feedback, queries, or need assistance, please don't hesitate to reach out to
@davanstrien
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## The TOMT-KIS-TRIPLETS (tip-of-my-tongue-known-item-search triplets) Dataset
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**TOMT-KIS-TRIPLETS** is a refined subset of the broader [TOMT-KIS](https://huggingface.co/datasets/webis/tip-of-my-tongue-known-item-search/) dataset, curated for advanced applications. Given that Wikipedia and IMDb are besides YouTube the most commonly appearing domains in links on the answer path (also see in TOMT-KIS the column `links_on_answer_path`), we focus specifically on these sources for higher relevancy and usability. By leveraging a Wikipedia dump and [SPARQL Wikipedia Query Service](https://query.wikidata.org), our objective is to develop a labeled dataset that contains direct links to relevant Wikipedia articles, making it ideal for supervised learning tasks.
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language:
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- en
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---
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## The TOMT-KIS-TRIPLETS (tip-of-my-tongue-known-item-search triplets) Dataset
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**TOMT-KIS-TRIPLETS** is a refined subset of the broader [TOMT-KIS](https://huggingface.co/datasets/webis/tip-of-my-tongue-known-item-search/) dataset, curated for advanced applications. Given that Wikipedia and IMDb are besides YouTube the most commonly appearing domains in links on the answer path (also see in TOMT-KIS the column `links_on_answer_path`), we focus specifically on these sources for higher relevancy and usability. By leveraging a Wikipedia dump and [SPARQL Wikipedia Query Service](https://query.wikidata.org), our objective is to develop a labeled dataset that contains direct links to relevant Wikipedia articles, making it ideal for supervised learning tasks.
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