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matentzn avatar matentzn commented on June 11, 2024

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

https://github.com/obophenotype/upheno-dev/blob/master/src/curation/pattern-matches/hp/abnormalMorphologyOfAnatomicalEntity.tsv

The goal would be to:

  1. Use Phenio KG, patterns and known matches (potentially) as background knowledge
  2. 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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caufieldjh avatar caufieldjh commented on June 11, 2024

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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matentzn avatar matentzn commented on June 11, 2024

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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cmungall avatar cmungall commented on June 11, 2024

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matentzn avatar matentzn commented on June 11, 2024

No I did not! I put it on our Agenda.

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cmungall avatar cmungall commented on June 11, 2024

Table 4:

image

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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