Triple
T2510857
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Rough Collie |
E52694
|
entity |
| Predicate | commonHealthIssues |
P4720
|
FINISHED |
| Object | collie eye anomaly |
—
|
LITERAL FINISHED |
How this triple was built (2 steps)
Every LLM step that produced this triple, in pipeline order — named-entity classification, the disambiguation choices (the exact options shown, with the pick highlighted), and the generated description. The batch + timestamp of each is in the Provenance table below.
NER
Named-entity recognition
gpt-5-mini
Instruction
Given a phrase, classify it is english named entity (e.g., persons, organizations, works of art) in Latin script, or not (e.g., literals, dates, URLs, verbose phrases). For disambiguation, the statement where the phrase occurs as object is also given. Please return a JSON object with `phrase` (string, the phrase being analyzed) and `is_ne` (boolean, indicating whether the phrase is a Named Entity).
Input
Phrase: collie eye anomaly | Statement: [Rough Collie, commonHealthIssues, collie eye anomaly]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: commonHealthIssues Context triple: [Rough Collie, commonHealthIssues, collie eye anomaly]
-
A.
hasHealthConcern
chosen
Indicates that an entity has a specific health-related issue, condition, or concern associated with it.
-
B.
diseaseType
Indicates that one entity is classified as a specific type or category of disease in relation to another entity.
-
C.
healthIndicator
Indicates a measure or signal that reflects the health status or condition of an entity.
-
D.
conditions
Indicates that one entity specifies or imposes requirements, constraints, or circumstances that must be satisfied or hold true for another entity or situation.
-
E.
healthEffect
Indicates the impact or consequence that one entity has on the health or well-being of another.
- F. None of above.
Provenance (3 batches)
The batch behind each pipeline step, in order, with when it ran. Timestamps are batch-level — stages were processed in waves, so the object chain (NER → NED1 → NEDg → NED2) reads in order, but predicate / elicitation batches can sit in a different wave.
| Step | Stage | Batch ID | Status | When |
|---|---|---|---|---|
| creating | Elicitation | batch_69ab4958e76481908a235377dd921c9e |
completed | March 6, 2026, 9:38 p.m. |
| NER | Named-entity recognition | batch_69abd5a33234819082ad49fa6594b6be |
completed | March 7, 2026, 7:37 a.m. |
| PD | Predicate disambiguation | batch_69abd0bf37c0819088d28b5081ba7556 |
completed | March 7, 2026, 7:16 a.m. |
Created at: March 6, 2026, 9:46 p.m.