Triple
T7795061
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Roosevelt dime |
E180277
|
entity |
| Predicate | silverContentPre1965 |
P16789
|
FINISHED |
| Object | 0.07234 troy ounces of 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: 0.07234 troy ounces of silver | Statement: [Roosevelt dime, silverContentPre1965, 0.07234 troy ounces of silver]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: silverContentPre1965 Context triple: [Roosevelt dime, silverContentPre1965, 0.07234 troy ounces of silver]
-
A.
legalTenderStatusAfter1933
Indicates whether something retained or acquired the status of legal tender following the monetary and legal changes implemented after the year 1933.
-
B.
changedSilverContentOf
Indicates that one entity altered the amount or proportion of silver contained in another entity.
-
C.
silverWeight
Indicates the weight or mass of an entity measured specifically in silver.
-
D.
silverContentStandard
chosen
Indicates the standard or required amount of silver content specified for something, such as a material, product, or item.
-
E.
denominationDepicted
Indicates that an item visually represents or shows the monetary denomination (value) of a currency.
- 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_69ca827d22208190b4dc5aa680edcf5d |
completed | March 30, 2026, 2:02 p.m. |
| NER | Named-entity recognition | batch_69caf78a6d88819093f83528fe88b182 |
completed | March 30, 2026, 10:22 p.m. |
| PD | Predicate disambiguation | batch_69cae9111b2481909684a2d4aa4831c2 |
completed | March 30, 2026, 9:20 p.m. |
Created at: March 30, 2026, 4:31 p.m.