Triple
T2814907
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Multi-Ethnic Study of Atherosclerosis |
E54258
|
entity |
| Predicate | approximateSampleSize |
P3846
|
FINISHED |
| Object | 6800 |
—
|
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: 6800 | Statement: [Multi-Ethnic Study of Atherosclerosis, approximateSampleSize, 6800]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: approximateSampleSize Context triple: [Multi-Ethnic Study of Atherosclerosis, approximateSampleSize, 6800]
-
A.
typicalSampleSizeRuleOfThumb
Indicates a heuristic guideline that specifies a commonly recommended sample size to use in typical situations or standard study designs.
-
B.
approximateSize
Indicates that one entity has a size that is roughly or approximately equal to the size of another entity.
-
C.
approximateAudienceSize
chosen
Indicates an estimated number of individuals or entities that are expected to be reached or affected in a given context.
-
D.
approximateCapacity
Indicates that one entity has an estimated or rough capacity value relative to another or to a specified measure.
-
E.
approximateRadius
Indicates that one entity specifies or provides an estimated value for the radius of 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_69ab49de0af08190b3da69683be1e728 |
completed | March 6, 2026, 9:40 p.m. |
| NER | Named-entity recognition | batch_69abde4d29488190a32461906dd9ea7e |
completed | March 7, 2026, 8:14 a.m. |
| PD | Predicate disambiguation | batch_69abdd0740208190911dc9c9546a79ae |
completed | March 7, 2026, 8:08 a.m. |
Created at: March 6, 2026, 9:59 p.m.