Triple
T5162362
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Montauban cemetery |
E116464
|
entity |
| Predicate | locatedIn |
P40
|
FINISHED |
| Object | Montauban |
E112838
|
NE 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: Montauban | Statement: [Montauban cemetery, locatedIn, Montauban]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Montauban Context triple: [Montauban cemetery, locatedIn, Montauban]
-
A.
Montauban
chosen
Montauban is a historic city in southern France known for its red-brick architecture and role as the capital of the Tarn-et-Garonne department.
-
B.
Gradignan
Gradignan is a suburban commune in southwestern France’s Gironde department, forming part of the Bordeaux metropolitan area and known for its green spaces and wine-growing surroundings.
-
C.
Pont-Saint-Esprit
Pont-Saint-Esprit is a historic commune in southern France, known for its medieval bridge over the Rhône River and its location in the Gard department of the Occitanie region.
-
D.
La Grande-Motte
La Grande-Motte is a seaside resort town on France’s Mediterranean coast, noted for its distinctive modernist pyramid-shaped architecture and beaches.
-
E.
Épinal
Épinal is a historic town in northeastern France, known for its traditional image-printing industry and picturesque setting in the Vosges region.
- F. None of above.
- G. Unsure - the case is ambiguous/there is not enough information to decide.
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_69bd445edb3881909b93b34d260717fc |
completed | March 20, 2026, 12:58 p.m. |
| NER | Named-entity recognition | batch_69bd79268ea48190a22d3350babc153c |
completed | March 20, 2026, 4:43 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69bed933abd88190981cb16189685b8f |
completed | March 21, 2026, 5:45 p.m. |
Created at: March 20, 2026, 1:44 p.m.