Triple
T23497014
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | France Télécom |
E571729
|
entity |
| Predicate | notableSubsidiary |
P9212
|
FINISHED |
| Object | Orange France |
—
|
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: Orange France | Statement: [France Télécom, notableSubsidiary, Orange France]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Orange France Context triple: [France Télécom, notableSubsidiary, Orange France]
-
A.
Orange France
chosen
Orange France is a major French telecommunications operator providing mobile, internet, and other communication services across France.
-
B.
Lafrançaise, France
Lafrançaise is a small commune in the Tarn-et-Garonne department of southern France, known for its rural charm and traditional French village atmosphere.
-
C.
de France
"de France" is a dynastic surname historically used by members of the French royal family, particularly the legitimate children of reigning kings of France.
-
D.
Nice, France
Nice, France is a major Mediterranean coastal city on the French Riviera known for its picturesque Promenade des Anglais, vibrant arts scene, and historic old town.
-
E.
Telfrance
Telfrance is a French television production company best known for creating and producing popular TV series and other audiovisual content.
- F. None of above.
- G. Unsure - the case is ambiguous/there is not enough information to decide.
Provenance (2 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_69e245b4829881909b77a70e942bbd54 |
completed | April 17, 2026, 2:37 p.m. |
| NER | Named-entity recognition | batch_69f1a7e0c5a48190badb8303f40f6180 |
completed | April 29, 2026, 6:40 a.m. |
Created at: April 17, 2026, 6:05 p.m.