Triple
T28919705
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Le Grand Jeu |
E733472
|
entity |
| Predicate | modeOfRepresentation |
P21655
|
FINISHED |
| Object | imagistic |
—
|
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: imagistic | Statement: [Le Grand Jeu, modeOfRepresentation, imagistic]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: modeOfRepresentation Context triple: [Le Grand Jeu, modeOfRepresentation, imagistic]
-
A.
representationType
chosen
Indicates the specific form or mode in which something is represented or expressed (e.g., as a symbol, image, model, or description).
-
B.
representationIn
Indicates that one entity serves as a depiction, model, or stand-in for another entity within a given context or medium.
-
C.
representationSystem
Indicates a system or framework used to represent, encode, or symbolize information, concepts, or entities.
-
D.
iconographicRepresentation
Indicates that one entity serves as a visual or symbolic depiction of another, typically in an artistic, religious, or cultural context.
-
E.
modalityOf
Indicates that one element specifies the manner, mood, or mode in which the action, event, or state expressed by another element is realized or presented.
- 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_69f05b0a5cc0819094828367ae204b70 |
completed | April 28, 2026, 7 a.m. |
| NER | Named-entity recognition | batch_69f65b19e61481909162ff801e90d95b |
completed | May 2, 2026, 8:14 p.m. |
| PD | Predicate disambiguation | batch_69f659d02f1c8190831758ac52bb54e4 |
completed | May 2, 2026, 8:08 p.m. |
Created at: April 28, 2026, 8:18 a.m.