Triple
T32366737
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | TENAYA |
E827013
|
entity |
| Predicate | conditionCategory |
P129457
|
FINISHED |
| Object | age-related macular degeneration |
—
|
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: age-related macular degeneration | Statement: [TENAYA, conditionCategory, age-related macular degeneration]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: conditionCategory Context triple: [TENAYA, conditionCategory, age-related macular degeneration]
-
A.
conditions
Indicates that one entity specifies or imposes requirements, constraints, or circumstances that must be satisfied or hold true for another entity or situation.
-
B.
clinicalCondition
chosen
Indicates that one entity has, exhibits, or is associated with a particular medical or health-related condition described by the other entity.
-
C.
eligibilityCategory
Indicates the classification or type of eligibility that applies to an entity within a given context.
-
D.
conditionsDescribedAs
Indicates that one entity is described or characterized in terms of certain conditions specified by another entity.
-
E.
classificationTerm
Indicates that one entity serves as a categorical label or type used to classify or group another entity.
- 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_69f349166d548190887b412fe908e2f4 |
completed | April 30, 2026, 12:20 p.m. |
| NER | Named-entity recognition | batch_69f6d16f5cb881908eed141afaaa0b51 |
completed | May 3, 2026, 4:39 a.m. |
| PD | Predicate disambiguation | batch_69f6cfe45554819089cbbd538d992132 |
completed | May 3, 2026, 4:32 a.m. |
Created at: May 1, 2026, 12:50 a.m.