add new dataset

README.md

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+---
+pretty_name: "LAMA: LAnguage Model Analysis - BigScience version"
+annotations_creators:
+- machine-generated
+language_creators:
+- machine-generated
+languages:
+- en
+licenses:
+- cc-by-4.0
+multilinguality:
+- monolingual
+size_categories:
+  trex:
+  - 1M<n<10M
+source_datasets:
+task_categories:
+- text-retrieval
+- text-classification
+task_ids:
+- fact-checking-retrieval
+- text-classification-other-probing
+- text-scoring
+paperswithcode_id: lama
+---
+
+# Dataset Card for LAMA: LAnguage Model Analysis - a dataset for probing and analyzing the factual and commonsense knowledge contained in pretrained language models.
+
+## Table of Contents
+- [Dataset Description](#dataset-description)
+  - [Dataset Summary](#dataset-summary)
+  - [Supported Tasks and Leaderboards](#supported-tasks-and-leaderboards)
+  - [Languages](#languages)
+- [Dataset Structure](#dataset-structure)
+  - [Data Instances](#data-instances)
+  - [Data Fields](#data-fields)
+  - [Data Splits](#data-splits)
+- [Dataset Creation](#dataset-creation)
+  - [Curation Rationale](#curation-rationale)
+  - [Source Data](#source-data)
+  - [Annotations](#annotations)
+  - [Personal and Sensitive Information](#personal-and-sensitive-information)
+- [Considerations for Using the Data](#considerations-for-using-the-data)
+  - [Social Impact of Dataset](#social-impact-of-dataset)
+  - [Discussion of Biases](#discussion-of-biases)
+  - [Other Known Limitations](#other-known-limitations)
+- [Additional Information](#additional-information)
+  - [Dataset Curators](#dataset-curators)
+  - [Licensing Information](#licensing-information)
+  - [Citation Information](#citation-information)
+
+## Dataset Description
+
+- **Homepage:**
+https://github.com/facebookresearch/LAMA
+- **Repository:**
+https://github.com/facebookresearch/LAMA
+- **Paper:**
+@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}
+}
+
+### 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}
+}
+

dataset_infos.json

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