Triple
T31827581
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Musée de l’Image d’Épinal |
E812435
|
entity |
| Predicate | hasGenreInCollection |
P81115
|
FINISHED |
| Object | religious imagery |
—
|
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: religious imagery | Statement: [Musée de l’Image d’Épinal, hasGenreInCollection, religious imagery]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasGenreInCollection Context triple: [Musée de l’Image d’Épinal, hasGenreInCollection, religious imagery]
-
A.
includedInGenreCollection
chosen
Indicates that something is a member of, or contained within, a specific genre-based collection.
-
B.
hasGenreInPortfolio
Indicates that an entity (such as a creator, label, or catalog) includes a particular genre within its body of work or offerings.
-
C.
hasTargetGenreCategory
Indicates that something is associated with or classified under a specific target genre category.
-
D.
hasGenreRelation
Indicates that there is an association between an entity and a specific genre, specifying the type or category it belongs to.
-
E.
hasGenreInSeries
Indicates that a particular genre is associated with, or applies to, a work as it appears within a specific series.
- 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_69f348e97fa48190aa06286962af6dee |
completed | April 30, 2026, 12:19 p.m. |
| NER | Named-entity recognition | batch_69fcd867f36081908c88c55a6a1404c1 |
completed | May 7, 2026, 6:22 p.m. |
| PD | Predicate disambiguation | batch_69fcd1f47b188190b4cf4b4c748d9d03 |
completed | May 7, 2026, 5:55 p.m. |
Created at: April 30, 2026, 11:47 p.m.