Triple
T32196197
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | LUCERNE |
E822410
|
entity |
| Predicate | hasConditionCategory |
P1255
|
FINISHED |
| Object | retinal disease |
—
|
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: retinal disease | Statement: [LUCERNE, hasConditionCategory, retinal disease]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasConditionCategory Context triple: [LUCERNE, hasConditionCategory, retinal disease]
-
A.
hasCondition
chosen
Indicates that an entity possesses, experiences, or is affected by a particular condition or state.
-
B.
haveCategoryCode
Indicates that an entity is associated with a specific classification or category identified by a code.
-
C.
containsCondition
Indicates that one entity includes, embodies, or is associated with a particular condition.
-
D.
hasCategoryOn
Indicates that something is assigned to or associated with a specific category within a given context or scope.
-
E.
canCondition
Indicates that one entity has the capability or potential to impose, apply, or bring about a particular condition on another entity or situation.
- 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_69f349093174819086e633c190a51aa8 |
completed | April 30, 2026, 12:20 p.m. |
| NER | Named-entity recognition | batch_6a037c894b488190bcbec2eccaff4a01 |
completed | May 12, 2026, 7:16 p.m. |
| PD | Predicate disambiguation | batch_6a0379eaa540819095a1c5d9f3513f9b |
completed | May 12, 2026, 7:05 p.m. |
Created at: May 1, 2026, 12:36 a.m.