Triple
T26175519
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Behçet |
E654528
|
entity |
| Predicate | hasEponymousDisease |
P160014
|
FINISHED |
| Object | Behçet's disease |
—
|
NE NERFINISHED |
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: Behçet's disease | Statement: [Behçet, hasEponymousDisease, Behçet's disease]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasEponymousDisease Context triple: [Behçet, hasEponymousDisease, Behçet's disease]
-
A.
hasAssociatedDisease
Indicates that an entity is linked to, or commonly occurs with, a particular disease or medical condition.
-
B.
hasTargetDisease
Indicates that an entity (such as a treatment, study, or intervention) is directed toward, intended to affect, or primarily concerned with a specified disease.
-
C.
diseaseName
Indicates that the associated value specifies the name or designation of a particular disease.
-
D.
causesDiseaseType
Indicates that one entity is responsible for causing a specific type or category of disease in another entity.
-
E.
humanDisease
Indicates that the subject is a disease that affects humans.
- F. None of above. chosen
Provenance (4 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_69ee5b45873c81909499203612d05d07 |
completed | April 26, 2026, 6:36 p.m. |
| NER | Named-entity recognition | batch_69f60c6bc408819098c4288f77d75e38 |
completed | May 2, 2026, 2:38 p.m. |
| PD | Predicate disambiguation | batch_69f5b0021da88190bdd4cf2698c23edf |
completed | May 2, 2026, 8:04 a.m. |
| PDg | Predicate description generation | batch_69f5f6b32a8881909baa0db57b80d56a |
completed | May 2, 2026, 1:05 p.m. |
Created at: April 26, 2026, 8:37 p.m.