Triple
T23496997
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | France Télécom |
E571729
|
entity |
| Predicate | brand |
P1500
|
FINISHED |
| Object | Orange |
—
|
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 | Statement: [France Télécom, brand, Orange]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Orange Context triple: [France Télécom, brand, Orange]
-
A.
Orange
Orange is a small town in north-central Massachusetts known for its rural character, historic mill village roots, and location along the Millers River.
-
B.
Orange
chosen
Orange is a major French multinational telecommunications company providing mobile, internet, and other digital services across numerous countries.
-
C.
Orange
"Orange" is a Pulitzer Prize-winning composition by contemporary American composer Caroline Shaw, known for its inventive blend of classical and modern musical elements.
-
D.
Orange
Orange is a historic town in southeastern France best known for giving its name and origin to the Dutch royal House of Orange-Nassau.
-
E.
Orange
Orange is a small suburban village in Cuyahoga County, Ohio, known for its residential character and proximity to the Cleveland metropolitan area.
- 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.