Triple
T27461212
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Saint-Louis church of Colombey-les-Deux-Églises |
E692748
|
entity |
| Predicate | burialSiteNearbyOf |
P90545
|
FINISHED |
| Object | Charles de Gaulle |
—
|
NE NERFINISHED |
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: Charles de Gaulle | Statement: [Saint-Louis church of Colombey-les-Deux-Églises, burialSiteNearbyOf, Charles de Gaulle]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: burialSiteNearbyOf Context triple: [Saint-Louis church of Colombey-les-Deux-Églises, burialSiteNearbyOf, Charles de Gaulle]
-
A.
burialSiteNear
Indicates that the burial site of one entity is located geographically close to another entity.
-
B.
buriedNear
chosen
Indicates that one entity is interred or buried in close physical proximity to another entity.
-
C.
nearbyTomb
Indicates that one entity is located close to or in the immediate vicinity of a tomb.
-
D.
nearbyCemetery
Indicates that one entity is located close to or in the immediate vicinity of a cemetery.
-
E.
hasNearbyCemetery
Indicates that one entity is located close to, or in the immediate vicinity of, a cemetery associated with 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_69ef5207903881909427745cda05d27a |
completed | April 27, 2026, 12:09 p.m. |
| NER | Named-entity recognition | batch_69f6359e3d3c81909814e2f0a7fb0ea9 |
completed | May 2, 2026, 5:34 p.m. |
| PD | Predicate disambiguation | batch_69f631871c888190bf29466fe4254e51 |
completed | May 2, 2026, 5:16 p.m. |
Created at: April 27, 2026, 12:50 p.m.