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# Dataset Card for PopQA
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## Dataset Summary
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PopQA is a large-scale open-domain question answering (QA) dataset, consisting of 14k entity-centric QA pairs. Each question is created by converting a knowledge tuple retrieved from Wikidata using a template. Each question come with the original `subject_entitiey`, `object_entity`and `relationship_type` annotation, as well as Wikipedia monthly page views.
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## Languages
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The dataset contains samples in English only.
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## Dataset Structure
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### Data Instances
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- Size of downloaded dataset file: 5.2 MB
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## Data Fields
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- `id`: question id
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- `subj`: subject entity name
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- `prop`: relationship type
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- `obj`: object entity name
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- `subj_id`: Wikidata ID of the subject entity
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- `prop_id`: Wikidata relationship type ID
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- `obj_id`: Wikidata ID of the object entity
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- `s_aliases`: aliases of the subject entity
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- `o_aliases`: aliases of the object entity
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- `s_uri`: Wikidata URI of the subject entity
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- `o_uri`: Wikidata URI of the object entity
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- `s_wiki_title`: Wikipedia page title of the subject entity
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- `o_wiki_title`: Wikipedia page title of the object entity
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- `s_pop`: Wikipedia monthly pageview of the subject entity
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- `o_pop`: Wikipedia monthly pageview of the object entity
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- `question`: PopQA question
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- `possible_answers`: a list of the gold answers.
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## Citation Information
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```
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@article{ mallen2023llm_memorization ,
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title={When Not to Trust Language Models: Investigating Effectiveness and Limitations of Parametric and Non-Parametric Memories },
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author={ Mallen, Alex and Asai,Akari and Zhong, Victor and Das, Rajarshi and Hajishirzi, Hannaneh and Khashabi, Daniel},
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journal={ arXiv preprint },
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year={ 2022 }
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}
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```
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