Triple
T34102591
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Le Bouscat |
E874610
|
entity |
| Predicate | isInArrondissement |
P26130
|
FINISHED |
| Object | arrondissement of Bordeaux |
—
|
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: arrondissement of Bordeaux | Statement: [Le Bouscat, isInArrondissement, arrondissement of Bordeaux]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: isInArrondissement Context triple: [Le Bouscat, isInArrondissement, arrondissement of Bordeaux]
-
A.
hasArrondissement
chosen
Indicates a relationship where an administrative unit or locality is associated with, or belongs to, a specific arrondissement.
-
B.
hasAdjacentArrondissement
Indicates that one arrondissement is directly next to or shares a boundary with another arrondissement.
-
C.
hasNumberOfArrondissements
Indicates the relationship that specifies how many arrondissements (administrative districts) are associated with a given entity.
-
D.
situéeDansLeDépartement
Indicates that one entity is located within the administrative boundaries of a specific department.
-
E.
capitalOfArrondissement
Indicates that a place serves as the administrative capital (seat) of a specified arrondissement.
- 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_69f349a80d4481908527317d43f5c579 |
completed | April 30, 2026, 12:23 p.m. |
| NER | Named-entity recognition | batch_69f70c6bceb081909bbc2f65c0fe036c |
completed | May 3, 2026, 8:50 a.m. |
| PD | Predicate disambiguation | batch_69f70ac0170c819098e3b8e41d02efef |
completed | May 3, 2026, 8:43 a.m. |
Created at: May 1, 2026, 1:53 a.m.