Triple
T12620110
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Type 3 Indian Princess gold dollar |
E301355
|
entity |
| Predicate | obverseMotifType |
P8603
|
FINISHED |
| Object | allegorical female figure |
—
|
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: allegorical female figure | Statement: [Type 3 Indian Princess gold dollar, obverseMotifType, allegorical female figure]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: obverseMotifType Context triple: [Type 3 Indian Princess gold dollar, obverseMotifType, allegorical female figure]
-
A.
obverseDepiction
chosen
Indicates that one entity is depicted on the obverse (front) side of another, such as the front face of a coin or medal.
-
B.
obverseText
Indicates the text that appears on the front (obverse) side of an object, typically a coin or medal.
-
C.
obverseDesignIntroduced
Indicates that a particular obverse design (front side of an item, typically a coin or medal) was first put into official use at a specified time.
-
D.
badgeObverseDesign
Indicates the design or imagery that appears on the front (obverse) side of a badge.
-
E.
obverseScriptStyle
Indicates the style or design of the script used on the obverse (front) side of an object, such as a coin or medal.
- 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_69d7bdeaf49c8190b13800111fa77ea3 |
completed | April 9, 2026, 2:55 p.m. |
| NER | Named-entity recognition | batch_69d9617b07ec8190b714f04ae6654060 |
completed | April 10, 2026, 8:45 p.m. |
| PD | Predicate disambiguation | batch_69d960b195108190ac25bd95e644ace4 |
completed | April 10, 2026, 8:42 p.m. |
Created at: April 9, 2026, 5:13 p.m.