Triple
T16484604
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Franklin half dollar |
E400405
|
entity |
| Predicate | silverBullionContent |
P107905
|
FINISHED |
| Object | 0.36169 troy ounces of silver (approximate) |
—
|
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: 0.36169 troy ounces of silver (approximate) | Statement: [Franklin half dollar, silverBullionContent, 0.36169 troy ounces of silver (approximate)]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: silverBullionContent Context triple: [Franklin half dollar, silverBullionContent, 0.36169 troy ounces of silver (approximate)]
-
A.
silverContentStandard
Indicates the standard or required amount of silver content specified for something, such as a material, product, or item.
-
B.
silverWeight
Indicates the weight or mass of an entity measured specifically in silver.
-
C.
standardGoldContent
Indicates the specified standard or required amount of gold contained in something, typically as a measure of purity or value.
-
D.
nobleMetal
Indicates that the subject is classified as a noble (chemically inert and corrosion-resistant) metal.
-
E.
bullionVersionWeight
chosen
Indicates the weight associated with a specific version or form of bullion.
- 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_69d883813098819084f5409539723b59 |
completed | April 10, 2026, 4:58 a.m. |
| NER | Named-entity recognition | batch_69e32e05bf448190947b9da15fd29d0a |
completed | April 18, 2026, 7:08 a.m. |
| PD | Predicate disambiguation | batch_69e22706b0588190a48a951c5211a617 |
completed | April 17, 2026, 12:26 p.m. |
Created at: April 10, 2026, 5:13 a.m.