Fact Knowledge Stability Benchmark
Creative Commons Attribution 4.0 International (CC BY 4.0)

You are free to share and adapt this material for any purpose, including
commercially, provided you give appropriate credit, link to the licence, and
indicate if changes were made.

Full text: https://creativecommons.org/licenses/by/4.0/legalcode


UPSTREAM SOURCES AND THEIR TERMS
--------------------------------

The facts in this benchmark are derived from the datasets below. Their terms
continue to apply to the derived material; CC BY 4.0 was chosen because it is
compatible with all of them. Please cite the original datasets alongside this
one.

  CounterFact              MIT License
    Meng et al., "Locating and Editing Factual Associations in GPT" (2022)

  LAMA / T-REx             CC BY 4.0
    Petroni et al., "Language Models as Knowledge Bases?" (2019)
    ElSahar et al., "T-REx: A Large Scale Alignment of Natural Language with
    Knowledge Base Triples" (2018)

  LAMA / Google-RE         CC BY 4.0 (per the LAMA distribution)
  LAMA / ConceptNet        CC BY-SA 4.0 (ConceptNet 5)

  PopQA                    MIT License
    Mallen et al., "When Not to Trust Language Models" (2023)

  Wikidata                 CC0 1.0 (entity identifiers and aliases)

The T-REx and Wikidata5M subsets present in the candidate pool were dropped
before benchmark selection and are not represented in the distributed files.

The code under runner/ and metrics/ is released under the MIT License.