Triple
T7506134
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Renaissance (French political party) |
E177392
|
entity |
| Predicate | mainVehicleFor |
P61976
|
FINISHED |
| Object | Emmanuel Macron’s presidential majority |
—
|
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: Emmanuel Macron’s presidential majority | Statement: [Renaissance (French political party), mainVehicleFor, Emmanuel Macron’s presidential majority]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: mainVehicleFor Context triple: [Renaissance (French political party), mainVehicleFor, Emmanuel Macron’s presidential majority]
-
A.
mainVehicle
chosen
Indicates that one vehicle is the primary or most important vehicle associated with a given entity or context.
-
B.
intendedVehicle
Indicates that one entity is the vehicle that another entity plans or is meant to use.
-
C.
vehicleUsed
Indicates that a particular vehicle is utilized or employed in performing an action, event, or activity.
-
D.
starVehicleFor
Indicates that one entity serves as the primary or featured vehicle associated with another entity, such as a person, production, or event.
-
E.
vahanaOf
Indicates that one entity serves as the vehicle, mount, or means of transportation for another entity.
- 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_69c69f276b108190af2cc790b6554544 |
completed | March 27, 2026, 3:15 p.m. |
| NER | Named-entity recognition | batch_69c6f5b5fcd88190ab4ab0ba96a6aa4b |
completed | March 27, 2026, 9:25 p.m. |
| PD | Predicate disambiguation | batch_69c6f4d44e9481909813e073b194f6f4 |
completed | March 27, 2026, 9:21 p.m. |
Created at: March 27, 2026, 3:45 p.m.