Comments (6)
Pattern library: https://github.com/obophenotype/upheno/tree/master/src/patterns/dosdp-patterns
Some matches: https://github.com/obophenotype/upheno-dev/tree/master/src/curation/pattern-matches
which contains
The goal would be to:
- Use Phenio KG, patterns and known matches (potentially) as background knowledge
- generate tables like this https://github.com/obophenotype/upheno-dev/blob/master/src/curation/pattern-matches/hp/abnormalMorphologyOfAnatomicalEntity.tsv for all phenotypes that dont yet have one
something like that, didnt think this through
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Does this idea also include leveraging the LLM's ability to simulate inference of anatomical relationships, like "zebrafish don't have a jugular vein" - though that's also likely to be hallucination-prone
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I would hope so! But I didnt think that far. SInce the input are the existing phenotype terms, we dont need to worry that we feed terms that do not exist.
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No I did not! I put it on our Agenda.
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Table 4:
Unfortunately the dumb ontology importer I wrote for curategpt doesn't support subq (have I mentioned how much I hate subq?) so mp/hp are exempt from this analysis, but OBA gives you an example at the extreme end of postcomp.
One major limitation of the analysis is that we limited things to new terms to avoid test data leakage. But for some ontologies like go only a handful of new terms had ldefs, so the sample size is very small here and likely biased towards "easy" cases hence the somewhat contradictory better performance on GO than on a patternized ontology
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Related Issues (20)
- Best way to apply on large quantities of documents? HOT 18
- `parse_yaml_predictions` doesn't correctly get predicate HOT 2
- Followup on #353 - handle more cases when transforming to KGX
- Followup on #353 - support including annotations in schemas to model KGX output HOT 1
- Don't show errors about Azure if not using Azure
- Add template suggestion command
- Add grounding refiner option for SPIRES
- Add extraction template for MIRO checklist
- Add caching for mapper
- Update default model for OpenAI HOT 1
- Broken links in documentation
- Make missing API key errors more friendly
- Transient errors with Translator endpoint HOT 1
- OpenAI base URL HOT 1
- Running web-ontogpt yeilds an "Internal Server Error" HOT 15
- gpt-4o HOT 3
- Update options for embedding models
- UnboundLocalError: local variable 'normalized_id' referenced before assignment HOT 1
- Make it easier to use custom schemas HOT 3
- ERROR: Could not build wheels for adeft, which is required to install pyproject.toml-based projects HOT 1
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