Triple
T15037607
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | toonie |
E378516
|
entity |
| Predicate | hasObverseInscription |
P23868
|
FINISHED |
| Object | name of the monarch |
—
|
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: name of the monarch | Statement: [toonie, hasObverseInscription, name of the monarch]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasObverseInscription Context triple: [toonie, hasObverseInscription, name of the monarch]
-
A.
obverseDepiction
Indicates that one entity is depicted on the obverse (front) side of another, such as the front face of a coin or medal.
-
B.
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.
-
C.
obverseText
chosen
Indicates the text that appears on the front (obverse) side of an object, typically a coin or medal.
-
D.
obverseStyle
Indicates the artistic or design style used on the obverse (front) side of an object, such as a coin or medal.
-
E.
materialTypicallyInscribedOn
Indicates the material that is most commonly used as the surface or medium on which something is inscribed.
- 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_69d85cd46b2c819090d054c27787f677 |
completed | April 10, 2026, 2:13 a.m. |
| NER | Named-entity recognition | batch_69ded82cf3848190b0b2b6c9e65bc70b |
completed | April 15, 2026, 12:13 a.m. |
| PD | Predicate disambiguation | batch_69de9a69d7848190b2b4662dd30f20e9 |
completed | April 14, 2026, 7:50 p.m. |
Created at: April 10, 2026, 2:59 a.m.