Triple
T30087598
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | lenticulostriate arteries |
E764638
|
entity |
| Predicate | lesionType |
P169355
|
FINISHED |
| Object | Charcot–Bouchard microaneurysm |
—
|
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: Charcot–Bouchard microaneurysm | Statement: [lenticulostriate arteries, lesionType, Charcot–Bouchard microaneurysm]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: lesionType Context triple: [lenticulostriate arteries, lesionType, Charcot–Bouchard microaneurysm]
-
A.
lesionAssociatedWithSymptom
Indicates that a particular lesion is linked to, or occurs together with, a specific symptom.
-
B.
typicalLesionLobe
Indicates the brain lobe in which a particular lesion type most commonly or characteristically occurs.
-
C.
injuryType
Indicates the specific kind or category of injury associated with an entity or event.
-
D.
diseaseType
Indicates that one entity is classified as a specific type or category of disease in relation to another entity.
-
E.
infectionType
Indicates the specific category or nature of an infection associated with an entity or event.
- 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_69f22473c0fc8190a926a8051b3b378b |
completed | April 29, 2026, 3:32 p.m. |
| NER | Named-entity recognition | batch_69f67de7792c81909b5e4e812d143624 |
completed | May 2, 2026, 10:42 p.m. |
| PD | Predicate disambiguation | batch_69f678ce54b081908c26edfd49e39c60 |
completed | May 2, 2026, 10:21 p.m. |
| PDg | Predicate description generation | batch_69f67d31cc60819084f64bd056e1ea4d |
completed | May 2, 2026, 10:39 p.m. |
Created at: April 29, 2026, 7:04 p.m.