Triple
T13310877
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Old Arsenal (Ancien Arsenal) |
E317059
|
entity |
| Predicate | hasMosaicTheme |
P62774
|
FINISHED |
| Object | historical scenes of Geneva |
—
|
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: historical scenes of Geneva | Statement: [Old Arsenal (Ancien Arsenal), hasMosaicTheme, historical scenes of Geneva]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasMosaicTheme Context triple: [Old Arsenal (Ancien Arsenal), hasMosaicTheme, historical scenes of Geneva]
-
A.
hasMosaic
Indicates that one entity possesses, contains, or is decorated with a mosaic.
-
B.
hasMosaicsBy
Indicates that something contains or features mosaics that were created by a specified agent or creator.
-
C.
hasMotiveTheme
Indicates that an action, event, or situation is associated with a central motivating theme or underlying driving idea.
-
D.
hasThemeConnection
Indicates a relationship where one entity is linked to another through a shared or related theme, topic, or conceptual focus.
-
E.
hasThemeType
chosen
Indicates that something is associated with or characterized by a particular thematic category or type.
- 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_69d806b40ab4819094adf6c374f4811a |
completed | April 9, 2026, 8:06 p.m. |
| NER | Named-entity recognition | batch_69d99cfdc9388190af1fdd3cd4717bd8 |
completed | April 11, 2026, 12:59 a.m. |
| PD | Predicate disambiguation | batch_69d98f6babd88190a5d529df9584b9a4 |
completed | April 11, 2026, 12:01 a.m. |
Created at: April 9, 2026, 9:29 p.m.