Triple
T9524678
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Lewy bodies |
E229729
|
entity |
| Predicate | pathologicalRole |
P67524
|
FINISHED |
| Object | neuronal dysfunction |
—
|
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: neuronal dysfunction | Statement: [Lewy bodies, pathologicalRole, neuronal dysfunction]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: pathologicalRole Context triple: [Lewy bodies, pathologicalRole, neuronal dysfunction]
-
A.
pathologyFeature
Indicates that one entity is a pathological characteristic, sign, or abnormal finding associated with another entity in a medical or biological context.
-
B.
pathogenicity
Indicates that one entity has the capacity to cause disease or harmful pathological effects in another entity.
-
C.
roleInDiseaseCycle
chosen
Indicates the specific function or contribution an entity has within the progression, transmission, or maintenance of a disease over time.
-
D.
pathogenicMechanism
Indicates the specific biological process or mechanism through which an agent causes disease or pathological effects in a host.
-
E.
clinicalRole
Indicates the specific function, responsibility, or position an entity holds within a clinical or healthcare context.
- 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_69ca847870a881909d8d751a7d29da39 |
completed | March 30, 2026, 2:11 p.m. |
| NER | Named-entity recognition | batch_69cd9899f99481908d374528716027f8 |
completed | April 1, 2026, 10:13 p.m. |
| PD | Predicate disambiguation | batch_69cca56a3d088190bdc16670678fb6c6 |
completed | April 1, 2026, 4:56 a.m. |
Created at: March 30, 2026, 7:59 p.m.