Triple
T34957858
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Lifesigns |
E1008166
|
entity |
| Predicate | featuresMedicalCondition |
—
|
GENERATED |
| Object | Phage |
—
|
UNRECOGNIZED GENERATED |
How this triple was built (1 step)
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.
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: featuresMedicalCondition Context triple: [Lifesigns, featuresMedicalCondition, Phage]
-
A.
featuresDisease
Indicates that an entity exhibits, presents, or is characterized by a particular disease.
-
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.
clinicalSignOf
Indicates that one clinical sign is evidence or manifestation of a particular disease, condition, or underlying medical state.
-
D.
depictsMedicalCondition
Indicates that one entity visually represents or illustrates a particular medical condition affecting another entity or subject.
-
E.
diseaseType
Indicates that one entity is classified as a specific type or category of disease in relation to another entity.
- F. None of above.
Provenance (1 batch)
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_69f76dc69564819099e9e78aed6ff0a6 |
completed | May 3, 2026, 3:46 p.m. |
Created at: May 3, 2026, 4 p.m.