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### Dataset Summary
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PR is a phrase retrieval task with the goal of finding a phrase **t** in a given document **d** such that **t** is semantically similar to the query phrase, which is the paraphrase **q**<sub>1</sub> provided by annotators.
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We release two versions of PR: **PR-pass** and **PR-page**,
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While PR-pass contains 28,147 examples, PR-page contains slightly fewer examples (28,098) as we remove those trivial examples whose Wikipedia pages contain exactly the query phrase (in addition to the target phrase).
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Both datasets are split into 5K/3K/~20K for test/dev/train, respectively.
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### Contributions
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Thanks to [@ThangPM](https://github.com/ThangPM) for adding this dataset.
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### Dataset Summary
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PR is a phrase retrieval task with the goal of finding a phrase **t** in a given document **d** such that **t** is semantically similar to the query phrase, which is the paraphrase **q**<sub>1</sub> provided by annotators.
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We release two versions of PR: **PR-pass** and **PR-page**, i.e., datasets of 3-tuples (query **q**<sub>1</sub>, target phrase **t**, document **d**) where **d** is a random 11-sentence passage that contains **t** or an entire Wikipedia page.
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While PR-pass contains 28,147 examples, PR-page contains slightly fewer examples (28,098) as we remove those trivial examples whose Wikipedia pages contain exactly the query phrase (in addition to the target phrase).
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Both datasets are split into 5K/3K/~20K for test/dev/train, respectively.
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### Contributions
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Thanks to [@ThangPM](https://github.com/ThangPM) for adding this dataset.
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