Triple
T28737876
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Monument à la République |
E730849
|
entity |
| Predicate | lightingDesignRenovation |
P59881
|
FINISHED |
| Object | 2013 |
—
|
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: 2013 | Statement: [Monument à la République, lightingDesignRenovation, 2013]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: lightingDesignRenovation Context triple: [Monument à la République, lightingDesignRenovation, 2013]
-
A.
lightingDesignFor
Indicates a relationship where one entity is responsible for creating or specifying the lighting design used for another entity (such as a space, event, or production).
-
B.
lightingDesigner
Indicates that an entity is responsible for planning, creating, or supervising the lighting design for a production, event, or environment.
-
C.
renovationFeature
Indicates that an entity has a specific renovation-related characteristic, element, or improvement associated with it.
-
D.
renovationOccasion
Indicates the event, reason, or context that serves as the occasion for a renovation to take place.
-
E.
hasLightingImprovements
chosen
Indicates that an entity has enhancements or upgrades made to its lighting conditions or systems.
- 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_69f043eae0908190b28ce314686247d7 |
completed | April 28, 2026, 5:21 a.m. |
| NER | Named-entity recognition | batch_69f6576d1f18819099ee8d00516ff93f |
completed | May 2, 2026, 7:58 p.m. |
| PD | Predicate disambiguation | batch_69f651ada6048190a7b4a6981565dc3a |
completed | May 2, 2026, 7:34 p.m. |
Created at: April 28, 2026, 6:01 a.m.