ontology-term-resolution

Ontology Term Resolution

When to use

Any time an ontology identifier is about to be written down or trusted: annotating a metadata column, filling a submission template, auditing a table someone else produced, or checking whether an ID in an old file is still current.

The rule

Never write an ontology ID from memory, and never accept one without checking it.

Ontology IDs are memorable in form and arbitrary in detail. A plausible-looking UBERON:0002108 is a real term (small intestine) that is not the liver, and nothing downstream will catch the substitution — the ID is well-formed, the ontology is right, and the metadata is silently wrong. Reviewers cannot spot it either, which is why these errors persist into published datasets.

Every ID this skill emits comes from a live OLS lookup. Every ID it is handed gets verified. Bioregistry, Identifiers.org, ZOOMA, and Ontobee answer prefix, landing-page, and shorthand questions — they do not replace that OLS check.

Which service

Question	Script	Authority
What is the term for "left ventricle"?	scripts/resolve_terms.py	OLS
OLS missed lab shorthand (PBMC, WT)	scripts/map_terms.py, then validate_terms.py	ZOOMA proposes; OLS decides
Is EFO:0001067 real, current, correctly labelled?	scripts/validate_terms.py	OLS
Is HPO a real prefix? Does HP:notanid match the pattern?	scripts/lookup_prefix.py	Bioregistry
Which landing page should this CURIE open?	scripts/lookup_prefix.py	Identifiers.org + Ontobee URLs

All four scripts take single values or files, emit TSV or JSON, and need no packages beyond the standard library. Full traps for the non-OLS services are in references/companion-apis.md.

Resolve text to terms

cd skills/ontology-term-resolution/scripts

# one string, constrained to the ontology that should define it
python3 resolve_terms.py "liver" --ontology uberon

query   rank  curie           label  ontology  match_type   strategy  defining_ontology
liver   1     UBERON:0002107  liver  uberon    exact_label  exact     true

# a column of tissue names; anything not an exact hit is reported, not guessed
python3 resolve_terms.py --input tissues.txt --ontology uberon \
    --exact-only --format tsv -o resolved.tsv

# accept fuzzy fallbacks, then review the partial hits by hand
python3 resolve_terms.py "left ventrical of heart" --ontology uberon --top 3

The search escalates exact (label and synonym) → token → fulltext and stops at the first strategy that returns anything, reporting which one fired. --exact-only disables the ladder. --branch UBERON:0000465 restricts candidates to descendants of a term.

Read match_type before using a result. exact_label and exact_synonym are safe; partial means OLS returned its best guess for a string that does not exist as written, and needs a human decision. unresolved is a legitimate output — see references/curation-rules.md for the normalisations worth retrying first.

Validate existing IDs

python3 validate_terms.py UBERON:0002107 EFO:0001067 UBERON:9999999

id              status     actual_label                  ontology  replacement     detail
UBERON:0002107  ok         liver                         uberon
EFO:0001067     obsolete   obsolete_parasitic infection  efo       MONDO:0005135   obsolete; replaced by MONDO:0005135
UBERON:9999999  not_found                                                          no such term in the ontology this prefix names

Exit code is 1 if anything failed, 0 otherwise, 2 on usage or network trouble — so it works as a CI gate on a metadata file:

# id + label columns; catches IDs that exist but are labelled as something else
python3 validate_terms.py --input metadata.tsv --strict

# a tissue column must hold UBERON anatomical entities and nothing else
python3 validate_terms.py --input tissue_ids.tsv \
    --branch UBERON:0000465 --expect-ontology uberon

Status	Meaning	Verdict
ok	Exists, current, consistent with everything asserted	pass
matched_synonym	Claimed label is a synonym; primary label differs	warn
imported_only	Home ontology no longer asserts this ID	warn
not_a_class	Term is a property or individual	warn
not_found	No such term	fail
obsolete	Obsoleted; replacement gives the successor when one exists	fail
label_mismatch	ID and claimed label describe different things	fail
wrong_ontology	Right kind of ID, wrong ontology for this column	fail
wrong_branch	Not a descendant of the required root	fail
malformed_curie	Not of the form PREFIX:local	fail

--strict promotes warnings to failures.

Check a prefix or compact identifier

python3 lookup_prefix.py HP HPO HP:0001250 HPO:0001250

query        status          preferred_prefix  canonical_curie  pattern    detail
HP           ok              HP                                 ^\d{7}$
HPO          synonym_prefix  HP                                 ^\d{7}$    'HPO' is a synonym of preferred prefix HP
HP:0001250   ok              HP                HP:0001250       ^\d{7}$
HPO:0001250  synonym_prefix  HP                HP:0001250       ^\d{7}$    'HPO' is a synonym of preferred prefix HP

Bioregistry accepts synonym prefixes. Identifiers.org does not — HPO:0001250 is HTTP 400. Rewrite to the preferred prefix before handing a CURIE to OLS. Landing-page columns come from Bioregistry mappings (providers.miriam, mappings.ontobee), not from templating that preferred prefix: ORPHA:558 is a 400, orphanet:558 is a 200, and OBA has no Identifiers.org namespace at all. Empty cells mean the service does not host the prefix. This script does not say the term exists; that is still validate_terms.py.

Map lab shorthand (ZOOMA)

# after resolve_terms.py returned unresolved / partial
python3 map_terms.py PBMC --ontology cl --exact-only

--ontology is required. Unfiltered ZOOMA annotate returns FOODON, XAO, and BTO alongside UBERON for liver, all at HIGH confidence. HIGH/GOOD hits are candidates only — run validate_terms.py on every CURIE before writing it down.

API behaviour that will mislead you

These are verified against the live service and are the reason this skill ships scripts rather than a recipe. Full detail in references/ols4-api.md.

Trap	Consequence
exact=true is exact token matching	liver returns 161 hits in UBERON; adding queryFields=label returns 1
/search never returns is_obsolete or term_replaced_by	Named in fieldList they are dropped silently; only term detail can answer "is this ID still current"
ontology=efo returns MONDO and CL hits	Ontologies import each other; filter on the CURIE prefix yourself
The same term appears once per importing ontology	Deduplicate on obo_id, keep is_defining_ontology: true
The obo_id index has holes	MONDO:0000001 is live but unindexed by obo_id; an IRI fallback is required to avoid a false not_found
IRIs are not all OBO PURLs	EFO and Orphanet use their own namespaces — resolve IRIs, do not template them
OxO is retired	Returns HTML with HTTP 200; use term cross-references or SSSOM instead
A branch check does not exclude cell types from anatomy	CARO puts cell under anatomical structure; constrain the prefix too
ZOOMA without an ontology filter	liver returns 100+ HIGH hits across FOODON, XAO, BTO, UBERON
Identifiers.org synonym prefixes	HPO:0001250 is HTTP 400; Bioregistry accepted the same CURIE
Identifiers.org encoded colon	HP%3A0001250 is HTTP 400; the path must keep :
Bioregistry preferred_prefix is not the Identifiers.org namespace	ORPHA:558 is 400; orphanet:558 is 200. hp:0001250 and chebi:15377 are 400 because those namespaces embed the prefix in the LUI. Use providers.miriam from /api/reference/{CURIE}; omit the URL when that mapping is missing (OBA, XAO, ECTO)
Ontobee search	HTML page only — no JSON API; do not scrape it

Choosing the ontology

MONDO for disease, HP for phenotype, UBERON for tissue, CL for cell type, EFO for assay, ChEBI for compounds, NCBITaxon for organism, PATO for sex and for normal. Prefix-to-OLS-id mappings (HP is served as hp, Orphanet as ordo), branch roots for --branch, and the overlapping-ontology judgement calls are in references/ontology-registry.md.

Reporting results

Give the ID and the label, and say how each was matched. A table of bare IDs cannot be reviewed. State unresolved terms explicitly rather than filling them with the nearest hit.

References

• references/ols4-api.md — endpoints, parameters, response fields, and every verified OLS trap.
• references/companion-apis.md — Bioregistry, Identifiers.org, ZOOMA, and Ontobee: when to use each, and the traps that make an unfiltered or synonym-prefix call look successful.
• references/ontology-registry.md — prefix/ontology-id table, branch roots, which ontology owns which concept.
• references/curation-rules.md — candidate-selection procedure, normalisations to retry, auditing an existing table, obsolete terms, cross-ontology mapping.

Agent operating procedure

1. Check the environment. Confirm network access, API keys (if required) and the database's current API documentation and rate limits.
2. Pin down the inputs. Confirm formats, identifiers and parameters from the data or the user. Ask rather than guess any value that changes the result.
3. Run a small version first. Fetch a single known record and check the response format before bulk queries.
4. Execute the full task using the instructions and references above.
5. Validate the result. Identifiers resolve, record counts are reported, and the database version or access date is recorded.
6. Report. State what was run (versions, commands, parameters), what was checked, and what is still uncertain.

If this happens	Do this
HTTP 429 or 5xx errors	Respect rate limits with backoff, batch requests, and report partial results honestly.
A function, flag or endpoint in these instructions is missing in the installed version	Check the installed version's own documentation (help(), --help, official docs), adapt, and tell the user. Never invent an API.
A required input, identifier or parameter is ambiguous	Ask the user, or state the assumption explicitly before running.

Integrity rules

• Never fabricate results, parameters, identifiers, citations or statistics. If something cannot be run or verified, say so plainly.
• Never invent accession numbers, IDs or records; report 'not found' instead.
• Treat version-specific details here as possibly outdated: confirm them against the official documentation for the installed version.
• Ask before actions that cost money, consume shared GPUs or cloud quota, touch personal or patient data, or cannot be undone.