metadata

license: apache-2.0
task_categories:
  - text-classification
tags:
  - Ontologies
  - Subsumption Inference
  - Natural Language Inference
pretty_name: OntoLAMA
size_categories:
  - 1M<n<10M
language:
  - en

OntoLAMA: LAnguage Model Analysis for Ontology Subsumption Inference

Dataset Summary

OntoLAMA is a set of language model (LM) probing datasets for ontology subsumption inference. The work follows the "LMs-as-KBs" literature but focuses on conceptualised knowledge extracted from formalised KBs such as the OWL ontologies. Specifically, the subsumption inference (SI) task is introduced and formulated in the NLI style, where the sub-concept and the super-concept involved in a subsumption axiom are verbalised and fitted into a template to form the premise and hypothesis, respectively. The SI task is further divided into Atomic SI and Complex SI where the former involves only atomic named concepts and the latter involves complex concept expressions restricted to OWL 2 EL. Real-world ontologies of different scales and domains are used for constructing OntoLAMA and in total there are four Atomic SI datasets and two Complex SI datasets.

Supported Tasks and Leaderboards

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Languages

The text in the dataset is in English, as used in the source ontologies. The associated BCP-47 code is en.

Dataset Structure

Data Instances

A typical SI data point comprises a verbalised sub-concept v_sub_concept, a verbalised super-concept v_super_concept, a binary label indicating whether these two concepts have a subsumption relationship or not (with 1 referring to a positive subsumption), and a string representation of the original subsumption axiom before verbalisation.

An example in the Atomic SI dataset created from the Gene Ontology (GO) is as follows:

{
    'v_sub_concept': 'ctpase activity',
    'v_super_concept': 'ribonucleoside triphosphate phosphatase activity',
    'label': 1,
    'axiom': 'SubClassOf(<http://purl.obolibrary.org/obo/GO_0043273> <http://purl.obolibrary.org/obo/GO_0017111>)'
}

An example in the Complex SI dataset created from the Food Ontology (FoodOn) is as follows:

{
    'v_sub_concept': '...',
    'v_super_concept': '...',
    'label': 0,
    'axiom': ...,
    'anchor_axiom': ...,
}

Data Fields

v_sub_concept: verbalised sub-concept expression.
v_super_concept: verbalised super-concept expression.
label: a binary class label indicating whether two concepts really form a subsumption relationship (1 means yes).
axiom: a string representation of the original subsumption axiom which is useful for tracing back to the ontology.
anchor_axiom: (for complex SI only) a string representation of the anchor equivalence axiom used for sampling the axiom.

Data Splits

[Needs More Information]

Licensing Information

Apache License, Version 2.0

Citation Information

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