Triple
T2501477
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Montluçon |
E52473
|
entity |
| Predicate | isPartOf |
P10
|
FINISHED |
| Object | Bourbonnais |
E27574
|
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: Bourbonnais | Statement: [Montluçon, isPartOf, Bourbonnais]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Bourbonnais Context triple: [Montluçon, isPartOf, Bourbonnais]
-
A.
Bourbonnais
chosen
Bourbonnais is a historic province in central France that once formed the heartland of the powerful Bourbon family’s domains.
-
B.
Bressant
Bressant is a novel by American author Julian Hawthorne, known as one of his early works in 19th-century fiction.
-
C.
La Plaine
La Plaine is a village in the canton of Geneva, Switzerland, situated near the French border and served as a terminus by the regional railway network.
-
D.
Lorraine
Lorraine is a historical and cultural region in northeastern France known for its strategic location bordering Luxembourg, Germany, and Belgium, and for its mixed French-German heritage.
-
E.
Moulinois
Moulinois is the French term for an inhabitant or native of the town of Moulins in central France.
- 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_69ab4957b3a88190adf968ae0c1b931c |
completed | March 6, 2026, 9:38 p.m. |
| NER | Named-entity recognition | batch_69abd1c9f80c8190b40ada396e184e75 |
completed | March 7, 2026, 7:20 a.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69af1fa0e26481908e383a6d44b3f3d5 |
completed | March 9, 2026, 7:29 p.m. |
Created at: March 6, 2026, 9:46 p.m.