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v0.3.0

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@cmungall cmungall released this 03 Aug 00:06
· 1354 commits to main since this release
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Highlights

Generate-and-Extract Command

This release adds a new command generate-extract that composes two operations.

  • generate a natural language description
  • parse the NL description using SPIRES

Cell Type Use Case

(This use case based on a conversation with @dosumis)

For example, given a cell type such as Acinar Cell Of Salivary Gland
, generate a description using GPT describing many aspects of the cell type, from it's marker genes through to its function and diseases it is implicated in.

After that use the cell-type schema (https://w3id.org/ontogpt/cell_type) to extract this into structured form. As an optional next step use linkml-owl to generate OWL TBox axioms

Iterative generate-extract

The command can be executed in iterative mode - this will traverse the extracted subtypes with each iteration, gradually building up an ontology that is entirely generated from the "latent knowledge" in the LLM

Here is a screenshot of an ontology generated entirely using OntoGPT by traversing from "Interneuron" downwards:

image

There are many oddities about it, currently each iteration is independent so it has no way of knowing if it is has already made a concept, but an interesting proof of principle. The ugly pct-encoded labels indicate cases where it couldn't match to an existing concept in CL or other ontology, and may represent KB gaps to be filled

More thoughts here: cell type summaries

What's Changed

New Contributors

Full Changelog: v0.2.0...v0.3.0