Triple
T972852
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Alzheimer's disease |
E20980
|
entity |
| Predicate | prevalentIn |
P22713
|
FINISHED |
| Object | older adults |
—
|
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: older adults | Statement: [Alzheimer's disease, prevalentIn, older adults]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: prevalentIn Context triple: [Alzheimer's disease, prevalentIn, older adults]
-
A.
historicallyDominantIn
Indicates that one entity has held a position of prevailing power, influence, or control over another entity or within a particular domain during a past historical period.
-
B.
widelyUsedIn
Indicates that something is commonly or extensively utilized within a particular context, domain, or group.
-
C.
primaryRegionOfPopularity
Indicates the geographic region where something is most widely used, favored, or popular compared to other regions.
-
D.
commonInCountry
Indicates that something occurs frequently or is widespread within a specified country.
-
E.
usedInRegion
Indicates that something is utilized or applied within a specific geographic or administrative region.
- 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_69a493b33d2c81909c52c369d3ca8436 |
completed | March 1, 2026, 7:29 p.m. |
| NER | Named-entity recognition | batch_69a4b44c38f08190997e141d424e9e04 |
completed | March 1, 2026, 9:49 p.m. |
| PD | Predicate disambiguation | batch_69a4b2a6aa2c8190aebba71320ab678f |
completed | March 1, 2026, 9:41 p.m. |
| PDg | Predicate description generation | batch_69a4b38630848190bd3898a4f42018ad |
completed | March 1, 2026, 9:45 p.m. |
Created at: March 1, 2026, 7:40 p.m.