Triple
T11676370
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Order of Kutuzov, 1st class |
E277501
|
entity |
| Predicate | hasObverseDesignElement |
P8603
|
FINISHED |
| Object | portrait of Mikhail Kutuzov |
—
|
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: portrait of Mikhail Kutuzov | Statement: [Order of Kutuzov, 1st class, hasObverseDesignElement, portrait of Mikhail Kutuzov]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasObverseDesignElement Context triple: [Order of Kutuzov, 1st class, hasObverseDesignElement, portrait of Mikhail Kutuzov]
-
A.
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.
-
B.
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.
-
C.
badgeObverseDesign
Indicates the design or imagery that appears on the front (obverse) side of a badge.
-
D.
obverseText
Indicates the text that appears on the front (obverse) side of an object, typically a coin or medal.
-
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_69d6aafd0a448190b44da30af8c6c519 |
completed | April 8, 2026, 7:22 p.m. |
| NER | Named-entity recognition | batch_69d8a44504c48190b519765a83ff9c5e |
completed | April 10, 2026, 7:18 a.m. |
| PD | Predicate disambiguation | batch_69d88a77e6e88190b7519100bde76575 |
completed | April 10, 2026, 5:28 a.m. |
Created at: April 8, 2026, 9:40 p.m.