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--- |
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license: apache-2.0 |
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task_categories: |
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- text-classification |
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tags: |
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- Ontologies |
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- Subsumption Inference |
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- Natural Language Inference |
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pretty_name: OntoLAMA |
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size_categories: |
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- 1M<n<10M |
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language: |
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- en |
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dataset_info: |
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- config_name: schemaorg-atomic-SI |
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features: |
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- name: v_sub_concept |
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dtype: string |
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- name: v_super_concept |
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dtype: string |
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- name: label |
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dtype: |
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class_label: |
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names: |
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'0': negative_subsumption |
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'1': positive_subsumption |
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- name: axiom |
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dtype: string |
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splits: |
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num_examples: 404 |
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- name: test |
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num_examples: 2830 |
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download_size: 82558 |
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dataset_size: 516208 |
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- config_name: doid-atomic-SI |
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features: |
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- name: v_sub_concept |
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dtype: string |
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- name: v_super_concept |
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'0': negative_subsumption |
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- config_name: foodon-atomic-SI |
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features: |
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- name: v_sub_concept |
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dtype: string |
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- name: v_super_concept |
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dtype: string |
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- name: label |
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class_label: |
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names: |
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'0': negative_subsumption |
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- config_name: go-atomic-SI |
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- config_name: bimnli |
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features: |
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- name: premise |
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dtype: string |
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- name: hypothesis |
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dtype: string |
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- name: label |
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dtype: |
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names: |
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'0': contradiction |
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'1': entailment |
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features: |
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- name: v_sub_concept |
|
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|
- name: v_super_concept |
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--- |
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# OntoLAMA: LAnguage Model Analysis for Ontology Subsumption Inference |
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### Dataset Summary |
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OntoLAMA is a set of language model (LM) probing datasets for ontology subsumption inference. |
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The work follows the "LMs-as-KBs" literature but focuses on conceptualised knowledge extracted from formalised KBs such as the OWL ontologies. |
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Specifically, the subsumption inference (SI) task is introduced and formulated in the NLI style, where the sub-concept and the super-concept |
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involved in a subsumption axiom are verbalised and fitted into a template to form the premise and hypothesis, respectively. The SI task is |
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further divided into Atomic SI and Complex SI where the former involves only atomic named concepts and the latter involves complex concept |
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expressions restricted to OWL 2 EL. Real-world ontologies of different scales and domains are used for constructing OntoLAMA and in total |
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there are four Atomic SI datasets and two Complex SI datasets. |
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|
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### Languages |
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The text in the dataset is in English, as used in the source ontologies. The associated BCP-47 code is `en`. |
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|
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## Dataset Structure |
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### Data Instances |
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An example in the **Atomic SI** dataset created from the Gene Ontology (GO) is as follows: |
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``` |
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{ |
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'v_sub_concept': 'ctpase activity', |
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'v_super_concept': 'ribonucleoside triphosphate phosphatase activity', |
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'label': 1, |
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'axiom': 'SubClassOf(<http://purl.obolibrary.org/obo/GO_0043273> <http://purl.obolibrary.org/obo/GO_0017111>)' |
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} |
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``` |
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|
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An example in the **Complex SI** dataset created from the Food Ontology (FoodOn) is as follows: |
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``` |
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{ |
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'v_sub_concept': '...', |
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'v_super_concept': '...', |
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'label': 0, |
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'axiom': ..., |
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'anchor_axiom': ..., |
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} |
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``` |
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|
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An example in the **biMNLI** dataset created from the MNLI dataset is as follows: |
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``` |
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{ |
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'premise': 'At the turn of the 19th century Los Angeles and Salt Lake City were among the burgeoning metropolises of the new American West.', |
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'hypothesis': 'Salt Lake City was booming in the early 19th century.', |
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'label': 1 |
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} |
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``` |
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|
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### Data Fields |
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|
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#### SI Data Fields |
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- `v_sub_concept`: verbalised sub-concept expression. |
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- `v_super_concept`: verbalised super-concept expression. |
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- `label`: a binary class label indicating whether two concepts really form a subsumption relationship (`1` means yes). |
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- `axiom`: a string representation of the original subsumption axiom which is useful for tracing back to the ontology. |
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- `anchor_axiom`: (for complex SI only) a string representation of the anchor equivalence axiom used for sampling the `axiom`. |
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#### biMNLI Data Fields |
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- `premise`: inheritated from the MNLI dataset. |
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- `hypothesis`: inheritated from the MNLI dataset. |
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- `label`: a binary class label indicating `contradiction` (`0`) or `entailment` (`1`). |
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|
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### Data Splits |
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| Source | #Concepts | #EquivAxioms | #Dataset (Train/Dev/Test) | |
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|--------|-----------|--------------|--------------------------------------------------------------------------| |
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| schema | 894 | - | Atomic SI: 808/404/2,830 | |
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| doid | 11,157 | - | Atomic SI: 90,500/11,312/11,314 | |
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| foodon | 30,995 | 2,383 | Atomic SI: 768,486/96,060/96,062 <br /> Complex SI: 3,754/1,850/13,080 | |
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| go | 43,303 | 11,456 | Atomic SI: 772,870/96,608/96,610 <br /> Complex SI: ... | |
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| MNLI | - | - | biMNLI: 235,622/26,180/12,906 | |
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### Licensing Information |
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|
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Apache License, Version 2.0 |
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### Citation Information |
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``` |
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@article{he2023language, |
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title={Language Model Analysis for Ontology Subsumption Inference}, |
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author={He, Yuan and Chen, Jiaoyan and Jim{\'e}nez-Ruiz, Ernesto and Dong, Hang and Horrocks, Ian}, |
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journal={arXiv preprint arXiv:2302.06761}, |
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year={2023} |
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} |
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``` |
