Triple
T763227
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Grand maître de la Légion d'honneur |
E16115
|
entity |
| Predicate | zoneD'influence |
P2828
|
FINISHED |
| Object | France et étrangers décorés par la France |
—
|
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: France et étrangers décorés par la France | Statement: [Grand maître de la Légion d'honneur, zoneD'influence, France et étrangers décorés par la France]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: zoneD'influence Context triple: [Grand maître de la Légion d'honneur, zoneD'influence, France et étrangers décorés par la France]
-
A.
zone
Indicates that an entity is located within, associated with, or assigned to a particular geographic or conceptual area or zone.
-
B.
sphereOfInfluence
chosen
Indicates the area or domain within which an entity exerts significant control, impact, or authority over others.
-
C.
regionType
Indicates the classification or category of a region, specifying what kind of region it is (e.g., administrative, geographic, or functional).
-
D.
regionName
Indicates the name assigned to a specific geographic or administrative region.
-
E.
regionException
Indicates an exception or exclusion to a rule, condition, or classification that applies specifically to a certain region or set of regions.
- 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_69a493684ee48190bd43b7c78da4aec8 |
completed | March 1, 2026, 7:28 p.m. |
| NER | Named-entity recognition | batch_69a4a69c8c448190a036a04fd8fdd2c2 |
completed | March 1, 2026, 8:50 p.m. |
| PD | Predicate disambiguation | batch_69a4a506106081909ef97a679ff00a5a |
completed | March 1, 2026, 8:43 p.m. |
Created at: March 1, 2026, 7:37 p.m.