Triple
T5819099
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | United States silver coins under one dollar |
E129060
|
entity |
| Predicate | mintMarkUsage |
P17363
|
FINISHED |
| Object | letters indicating mint location |
—
|
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: letters indicating mint location | Statement: [United States silver coins under one dollar, mintMarkUsage, letters indicating mint location]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: mintMarkUsage Context triple: [United States silver coins under one dollar, mintMarkUsage, letters indicating mint location]
-
A.
mintMarkUsedOn
chosen
Indicates that a particular mint mark was applied to or appears on a specific coin or numismatic item.
-
B.
usedMark
Indicates that one entity has employed or applied a particular mark, symbol, or indicator in some context or action.
-
C.
usedReportingMarks
Indicates that an entity employed specific railroad reporting marks to identify rolling stock or operations.
-
D.
marksOn
Indicates that one entity bears visible signs, traces, or imprints that have been made or left by another entity.
-
E.
minorUnitUsage
Indicates how a minor or subordinate unit is used or functions in relation to a larger or primary unit.
- 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_69c0084869e881908d7859492183ca7b |
completed | March 22, 2026, 3:18 p.m. |
| NER | Named-entity recognition | batch_69c0400f1af881908d376ea4793f6dea |
completed | March 22, 2026, 7:16 p.m. |
| PD | Predicate disambiguation | batch_69c0333fdd7081908d829265caa2ac11 |
completed | March 22, 2026, 6:21 p.m. |
Created at: March 22, 2026, 3:53 p.m.