Triple
T13426521
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Draped Bust dollar |
E313494
|
entity |
| Predicate | diameterApproximate |
P7302
|
FINISHED |
| Object | 39 to 40 millimeters |
—
|
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: 39 to 40 millimeters | Statement: [Draped Bust dollar, diameterApproximate, 39 to 40 millimeters]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: diameterApproximate Context triple: [Draped Bust dollar, diameterApproximate, 39 to 40 millimeters]
-
A.
approximateDiameter
chosen
Indicates that one entity specifies the estimated or rough measurement of another entity’s diameter.
-
B.
approximateRadius
Indicates that one entity specifies or provides an estimated value for the radius of another entity.
-
C.
approximateLengthInMeters
Indicates the estimated or roughly measured length of something expressed in meters.
-
D.
hasDiameterClass
Indicates that an entity is associated with a specific category or range based on the size of its diameter.
-
E.
sphereDiameter
Indicates the measurement of the distance across a sphere passing through its center, relating the sphere to its diameter.
- 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_69d806ad0c44819088833ae1ec9e9690 |
completed | April 9, 2026, 8:06 p.m. |
| NER | Named-entity recognition | batch_69dbaed1f9208190bf5ef5b8a7ded376 |
completed | April 12, 2026, 2:40 p.m. |
| PD | Predicate disambiguation | batch_69d9a03926188190ab3948d1f5d3941f |
completed | April 11, 2026, 1:13 a.m. |
Created at: April 9, 2026, 9:40 p.m.