Triple
T33205116
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | erythema nodosum |
E849999
|
entity |
| Predicate | pathologyType |
P22707
|
FINISHED |
| Object | septal panniculitis without vasculitis |
—
|
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: septal panniculitis without vasculitis | Statement: [erythema nodosum, pathologyType, septal panniculitis without vasculitis]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: pathologyType Context triple: [erythema nodosum, pathologyType, septal panniculitis without vasculitis]
-
A.
pathologyFeature
chosen
Indicates that one entity is a pathological characteristic, sign, or abnormal finding associated with another entity in a medical or biological context.
-
B.
diseaseType
Indicates that one entity is classified as a specific type or category of disease in relation to another entity.
-
C.
targetsPathophysiology
Indicates that an intervention, agent, or process is specifically directed at modifying or influencing a particular disease mechanism or pathological process.
-
D.
pathogenType
Indicates the specific kind or category of pathogen associated with or responsible for an entity or condition.
-
E.
causesDiseaseType
Indicates that one entity is responsible for causing a specific type or category of disease in 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_69f3495efedc8190843a5728089544b9 |
completed | April 30, 2026, 12:21 p.m. |
| NER | Named-entity recognition | batch_69f6e02ba6b881908dfafc52d3b75f1c |
completed | May 3, 2026, 5:42 a.m. |
| PD | Predicate disambiguation | batch_69f6de09c2f481909f8b2545d3208c9f |
completed | May 3, 2026, 5:32 a.m. |
Created at: May 1, 2026, 1:30 a.m.