Dataset:

Task Categories: other
Languages: en
Multilinguality: monolingual
Size Categories: 10K<n<100K
Language Creators: expert-generated
Annotations Creators: expert-generated
Source Datasets: original

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Dataset Summary

The database is derived from the NCI PID Pathway Interaction Database, and the textual mentions are extracted from cooccurring pairs of genes in PubMed abstracts, processed and annotated by Literome (Poon et al. 2014). This dataset was used in the paper “Compositional Learning of Embeddings for Relation Paths in Knowledge Bases and Text” (Toutanova, Lin, Yih, Poon, and Quirk, 2016). More details can be found in the included README.

Supported Tasks and Leaderboards

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Languages

English

Dataset Structure

NCI-PID-PubMed Genomics Knowledge Base Completion Dataset

This dataset includes a database of regulation relationships among genes and corresponding textual mentions of pairs of genes in PubMed article abstracts. The database is derived from the NCI PID Pathway Interaction Database, and the textual mentions are extracted from cooccurring pairs of genes in PubMed abstracts, processed and annotated by Literome. This dataset was used in the paper "Compositional Learning of Embeddings for Relation Paths in Knowledge Bases and Text".

FILE FORMAT DETAILS

The files train.txt, valid.txt, and test.text contain the training, development, and test set knowledge base (database of regulation relationships) triples used in. The file text.txt contains the textual triples derived from PubMed via entity linking and processing with Literome. The textual mentions were used for knowledge base completion in.

The separator is a tab character; the relations are Positive_regulation, Negative_regulation, and Family (Family relationships occur only in the training set).

The format is:

| GENE1 | relation | GENE2 |

Example: ABL1 Positive_regulation CDK2

The separator is a tab character; the relations are Positive_regulation, Negative_regulation, and Family (Family relationships occur only in the training set).

Data Instances

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Data Fields

The format is:

| GENE1 | relation | GENE2 |

Data Splits

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Dataset Creation

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Curation Rationale

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Source Data

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Initial Data Collection and Normalization

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Who are the source language producers?

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Annotations

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Annotation process

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Who are the annotators?

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Personal and Sensitive Information

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Considerations for Using the Data

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Social Impact of Dataset

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Discussion of Biases

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Other Known Limitations

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Additional Information

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Dataset Curators

The dataset was initially created by Kristina Toutanova, Victoria Lin, Wen-tau Yih, Hoifung Poon and Chris Quirk, during work done at Microsoft Research.

Licensing Information

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Citation Information

@inproceedings{toutanova-etal-2016-compositional,
    title = "Compositional Learning of Embeddings for Relation Paths in Knowledge Base and Text",
    author = "Toutanova, Kristina  and
      Lin, Victoria  and
      Yih, Wen-tau  and
      Poon, Hoifung  and
      Quirk, Chris",
    booktitle = "Proceedings of the 54th Annual Meeting of the Association for Computational Linguistics (Volume 1: Long Papers)",
    month = aug,
    year = "2016",
    address = "Berlin, Germany",
    publisher = "Association for Computational Linguistics",
    url = "https://www.aclweb.org/anthology/P16-1136",
    doi = "10.18653/v1/P16-1136",
    pages = "1434--1444",
}

Contributions

Thanks to @manandey for adding this dataset.

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