Triple
T5819077
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | United States silver coins under one dollar |
E129060
|
entity |
| Predicate | typicalAlloy |
P26314
|
FINISHED |
| Object | 0.900 fine silver |
—
|
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: 0.900 fine silver | Statement: [United States silver coins under one dollar, typicalAlloy, 0.900 fine silver]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: typicalAlloy Context triple: [United States silver coins under one dollar, typicalAlloy, 0.900 fine silver]
-
A.
typicalValueForAluminum
Indicates the standard or commonly accepted value (such as a property or parameter) that is characteristic for aluminum in a given context.
-
B.
associatedMetal
chosen
Indicates a relationship where one entity is linked or connected to a particular metal, such as by composition, usage, origin, or symbolic association.
-
C.
allMetalConstruction
Indicates that something is constructed entirely or almost entirely from metal components.
-
D.
typicalValueForSteel
Indicates that a given value represents a standard or commonly expected value associated with steel under typical conditions.
-
E.
typicalIn
Indicates that something commonly occurs, appears, or is found within a given context, category, or environment.
- 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.