Triple
T972821
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Alzheimer's disease |
E20980
|
entity |
| Predicate | onsetTypicalAge |
P9036
|
FINISHED |
| Object | late adulthood |
—
|
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: late adulthood | Statement: [Alzheimer's disease, onsetTypicalAge, late adulthood]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: onsetTypicalAge Context triple: [Alzheimer's disease, onsetTypicalAge, late adulthood]
-
A.
hasOnset
chosen
Indicates the point in time or condition at which a process, event, or state begins.
-
B.
typicalEligibilityAge
Indicates the usual or standard age at which an entity qualifies for or becomes eligible for a particular status, benefit, or activity.
-
C.
ageAtStartOfReign
Indicates the age an individual was when they began their reign or rule.
-
D.
maturityRange
Indicates the span or limits of maturity (such as age, development stage, or readiness) within which the related entities or conditions are considered applicable.
-
E.
diagnosisYear
Indicates the calendar year in which a diagnosis was made or recorded for an 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_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. |
Created at: March 1, 2026, 7:40 p.m.