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Pianos Become the Teeth
P740
Baltimore
[X] was founded in [Y] .
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Where was [X] founded?
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Barren Earth
P740
Helsinki
[X] was founded in [Y] .
N-1
Where was [X] founded?
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SNCF
P740
Paris
[X] was founded in [Y] .
N-1
Where was [X] founded?
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Starwood Capital Group
P740
Greenwich
[X] was founded in [Y] .
N-1
Where was [X] founded?
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Clap Your Hands Say Yeah
P740
Philadelphia
[X] was founded in [Y] .
N-1
Where was [X] founded?
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Cocteau Twins
P740
Scotland
[X] was founded in [Y] .
N-1
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Odex
P740
Singapore
[X] was founded in [Y] .
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Swiss Federal Railways
P740
Bern
[X] was founded in [Y] .
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Scott Paper Company
P740
Philadelphia
[X] was founded in [Y] .
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Comerica
P740
Detroit
[X] was founded in [Y] .
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Lenovo
P740
Beijing
[X] was founded in [Y] .
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Melody Club
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Sweden
[X] was founded in [Y] .
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Chvrches
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Glasgow
[X] was founded in [Y] .
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The Boat People
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Brisbane
[X] was founded in [Y] .
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Where was [X] founded?
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Dragonette
P740
Toronto
[X] was founded in [Y] .
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Hostage Life
P740
Toronto
[X] was founded in [Y] .
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Coffin Break
P740
Seattle
[X] was founded in [Y] .
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Ganz Works
P740
Budapest
[X] was founded in [Y] .
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Iran Airtour
P740
Tehran
[X] was founded in [Y] .
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The Parlotones
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Johannesburg
[X] was founded in [Y] .
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Sweet Jesus
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Birmingham
[X] was founded in [Y] .
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German Alpine Club
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Munich
[X] was founded in [Y] .
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Ohbijou
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Toronto
[X] was founded in [Y] .
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Morton Salt
P740
Chicago
[X] was founded in [Y] .
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Armani
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Milan
[X] was founded in [Y] .
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Malaguti
P740
Bologna
[X] was founded in [Y] .
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Neko Entertainment
P740
Paris
[X] was founded in [Y] .
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The Moody Blues
P740
Birmingham
[X] was founded in [Y] .
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Kurt Vile
P740
Philadelphia
[X] was founded in [Y] .
N-1
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The Brothers Martin
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Riverside
[X] was founded in [Y] .
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The Besnard Lakes
P740
Montreal
[X] was founded in [Y] .
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Alfaguara
P740
Madrid
[X] was founded in [Y] .
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Hot Cross
P740
Philadelphia
[X] was founded in [Y] .
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Neon Christ
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Atlanta
[X] was founded in [Y] .
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Kakao M
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Seoul
[X] was founded in [Y] .
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Team Syachihoko
P740
Nagoya
[X] was founded in [Y] .
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Sweet Savage
P740
Belfast
[X] was founded in [Y] .
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Cook da Books
P740
Liverpool
[X] was founded in [Y] .
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Black Tide
P740
Miami
[X] was founded in [Y] .
N-1
Where was [X] founded?
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Hupmobile
P740
Detroit
[X] was founded in [Y] .
N-1
Where was [X] founded?
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Essanay Studios
P740
Chicago
[X] was founded in [Y] .
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Where was [X] founded?
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Popu Lady
P740
Taiwan
[X] was founded in [Y] .
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Where was [X] founded?
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Beechcraft
P740
Wichita
[X] was founded in [Y] .
N-1
Where was [X] founded?
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The Miserable Rich
P740
Brighton
[X] was founded in [Y] .
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Where was [X] founded?
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Pink Fairies
P740
London
[X] was founded in [Y] .
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Where was [X] founded?
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The Coca-Cola Company
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Atlanta
[X] was founded in [Y] .
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Givers
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[X] was founded in [Y] .
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The Gracious Few
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York
[X] was founded in [Y] .
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Archaeopress
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Oxford
[X] was founded in [Y] .
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Piranha Games
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Vancouver
[X] was founded in [Y] .
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Constantin Film
P740
Frankfurt
[X] was founded in [Y] .
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Where was [X] founded?
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The Answering Machine
P740
Manchester
[X] was founded in [Y] .
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The Mess Hall
P740
Sydney
[X] was founded in [Y] .
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E.Town Concrete
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Elizabeth
[X] was founded in [Y] .
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Ericsson
P740
Stockholm
[X] was founded in [Y] .
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Kasabian
P740
Leicester
[X] was founded in [Y] .
N-1
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Cronian
P740
Norway
[X] was founded in [Y] .
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Regis Corporation
P740
Minneapolis
[X] was founded in [Y] .
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RuPaul
P740
Atlanta
[X] was founded in [Y] .
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Where was [X] founded?
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Eisley
P740
Tyler
[X] was founded in [Y] .
N-1
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Stevie Wonder
P740
Detroit
[X] was founded in [Y] .
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Where was [X] founded?
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World Population Foundation
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Netherlands
[X] was founded in [Y] .
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Where was [X] founded?
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Fucked Up
P740
Toronto
[X] was founded in [Y] .
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Aiden
P740
Seattle
[X] was founded in [Y] .
N-1
Where was [X] founded?
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Tableau Software
P740
Seattle
[X] was founded in [Y] .
N-1
Where was [X] founded?
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Philadelphia Savings Fund Society
P740
Philadelphia
[X] was founded in [Y] .
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Where was [X] founded?
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Diamond Plate
P740
Chicago
[X] was founded in [Y] .
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Persian Risk
P740
Cardiff
[X] was founded in [Y] .
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Econoline Crush
P740
Vancouver
[X] was founded in [Y] .
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Mambo Taxi
P740
London
[X] was founded in [Y] .
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Where was [X] founded?
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Anarchy Club
P740
Boston
[X] was founded in [Y] .
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ReVamp
P740
Netherlands
[X] was founded in [Y] .
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The Xcerts
P740
Aberdeen
[X] was founded in [Y] .
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Rosneft
P740
Moscow
[X] was founded in [Y] .
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El-P
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Brooklyn
[X] was founded in [Y] .
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The Polyphonic Spree
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Dallas
[X] was founded in [Y] .
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Two Guys
P740
Harrison
[X] was founded in [Y] .
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The Fartz
P740
Seattle
[X] was founded in [Y] .
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Brain Records
P740
Hamburg
[X] was founded in [Y] .
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The Starlings
P740
London
[X] was founded in [Y] .
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Kasino
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Brazil
[X] was founded in [Y] .
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Givenchy
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Paris
[X] was founded in [Y] .
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The Agonist
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Montreal
[X] was founded in [Y] .
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J. G. Brill Company
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Philadelphia
[X] was founded in [Y] .
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Speedy Ortiz
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Northampton
[X] was founded in [Y] .
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The Pretty Things
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[X] was founded in [Y] .
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The Rattles
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Hamburg
[X] was founded in [Y] .
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The Walkabouts
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Seattle
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INXS
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Sydney
[X] was founded in [Y] .
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Fudge Tunnel
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Nottingham
[X] was founded in [Y] .
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Filippa K
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Sweden
[X] was founded in [Y] .
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CSR Limited
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Sydney
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Suez Environnement
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Paris
[X] was founded in [Y] .
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Fuck Buttons
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Bristol
[X] was founded in [Y] .
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Kill Rock Stars
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Olympia
[X] was founded in [Y] .
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Hollerado
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Ottawa
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Packard
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Warren
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This Town Needs Guns
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Oxford
[X] was founded in [Y] .
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Bremer Vulkan
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Bremen
[X] was founded in [Y] .
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Was (Not Was)
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Detroit
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Dataset Card for LAMA: LAnguage Model Analysis - a dataset for probing and analyzing the factual and commonsense knowledge contained in pretrained language models.

@inproceedings{petroni2020how, title={How Context Affects Language Models' Factual Predictions}, author={Fabio Petroni and Patrick Lewis and Aleksandra Piktus and Tim Rockt{"a}schel and Yuxiang Wu and Alexander H. Miller and Sebastian Riedel}, booktitle={Automated Knowledge Base Construction}, year={2020}, url={https://openreview.net/forum?id=025X0zPfn} }

Dataset Summary

This dataset provides the data for LAMA. This dataset only contains TRex (subset of wikidata triples).

The dataset includes some cleanup, and addition of a masked sentence and associated answers for the [MASK] token. The accuracy in predicting the [MASK] token shows how well the language model knows facts and common sense information. The [MASK] tokens are only for the "object" slots.

This version also contains questions instead of templates that can be used to probe also non-masking models.

See the paper for more details. For more information, also see: https://github.com/facebookresearch/LAMA

Languages

en

Dataset Structure

Data Instances

The trex config has the following fields:

{'uuid': 'a37257ae-4cbb-4309-a78a-623036c96797', 'sub_label': 'Pianos Become the Teeth', 'predicate_id': 'P740', 'obj_label': 'Baltimore', 'template': '[X] was founded in [Y] .', 'type': 'N-1', 'question': 'Where was [X] founded?'} 34039

Data Splits

There are no data splits.

Dataset Creation

Curation Rationale

This dataset was gathered and created to probe what language models understand.

Source Data

Initial Data Collection and Normalization

See the reaserch paper and website for more detail. The dataset was created gathered from various other datasets with cleanups for probing.

Who are the source language producers?

The LAMA authors and the original authors of the various configs.

Annotations

Annotation process

Human annotations under the original datasets (conceptnet), and various machine annotations.

Who are the annotators?

Human annotations and machine annotations.

Personal and Sensitive Information

Unkown, but likely names of famous people.

Considerations for Using the Data

Social Impact of Dataset

The goal for the work is to probe the understanding of language models.

Discussion of Biases

Since the data is from human annotators, there is likely to be baises.

[More Information Needed]

Other Known Limitations

The original documentation for the datafields are limited.

Additional Information

Dataset Curators

The authors of LAMA at Facebook and the authors of the original datasets.

Licensing Information

The Creative Commons Attribution-Noncommercial 4.0 International License. see https://github.com/facebookresearch/LAMA/blob/master/LICENSE

Citation Information

@inproceedings{petroni2019language, title={Language Models as Knowledge Bases?}, author={F. Petroni, T. Rockt{"{a}}schel, A. H. Miller, P. Lewis, A. Bakhtin, Y. Wu and S. Riedel}, booktitle={In: Proceedings of the 2019 Conference on Empirical Methods in Natural Language Processing (EMNLP), 2019}, year={2019} }

@inproceedings{petroni2020how, title={How Context Affects Language Models' Factual Predictions}, author={Fabio Petroni and Patrick Lewis and Aleksandra Piktus and Tim Rockt{"a}schel and Yuxiang Wu and Alexander H. Miller and Sebastian Riedel}, booktitle={Automated Knowledge Base Construction}, year={2020}, url={https://openreview.net/forum?id=025X0zPfn} }

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