Triple
T12362849
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Fort-Royal |
E294783
|
entity |
| Predicate | formerNameOf |
P65
|
FINISHED |
| Object | Fort-de-France |
E221136
|
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: Fort-de-France | Statement: [Fort-Royal, formerNameOf, Fort-de-France]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Fort-de-France Context triple: [Fort-Royal, formerNameOf, Fort-de-France]
-
A.
Fort-de-France
chosen
Fort-de-France is the largest city and administrative, economic, and cultural center of the French Caribbean island of Martinique.
-
B.
La Flèche
La Flèche is a historic town in western France known for its royal heritage, educational institutions, and the renowned Zoo de La Flèche.
-
C.
Fontaine-au-Bois
Fontaine-au-Bois is a small commune in the Nord department of northern France, situated within the administrative area of the Hauts-de-France region.
-
D.
Fontenay-le-Comte
Fontenay-le-Comte is a historic town in western France known as an administrative and cultural center in the Vendée department.
-
E.
Tallard
Tallard is a French surname most notably associated with Camille d'Hostun, duc de Tallard, a marshal of France during the War of the Spanish Succession.
- 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_69d6ab6d8a4081908636601e69ddf262 |
completed | April 8, 2026, 7:24 p.m. |
| NER | Named-entity recognition | batch_69d93f91a1908190a8a4fa9da3b47933 |
completed | April 10, 2026, 6:21 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69f65ea0a4c4819091a7a66c3b73d776 |
completed | May 2, 2026, 8:29 p.m. |
Created at: April 8, 2026, 9:54 p.m.