Triple
T8611315
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | AirPrint |
E203919
|
entity |
| Predicate | usesProtocol |
P203
|
FINISHED |
| Object | Bonjour |
E200281
|
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: Bonjour | Statement: [AirPrint, usesProtocol, Bonjour]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Bonjour Context triple: [AirPrint, usesProtocol, Bonjour]
-
A.
Bonjour
chosen
Bonjour is Apple’s zero-configuration networking technology that enables automatic discovery of devices and services on local IP networks.
-
B.
Salutati
Salutati is an Italian surname most notably associated with Coluccio Salutati, a leading 14th-century humanist and Chancellor of Florence.
-
C.
Bienvenues
Bienvenues is a renowned component of the name of the prestigious Burgundy Grand Cru white wine Bienvenues-Bâtard-Montrachet.
-
D.
Bonne
Bonne of Berry was a 14th-century French noblewoman of the House of Valois, daughter of John II of France and a politically significant figure through her dynastic marriages.
-
E.
Hello
"Hello" is a globally successful power ballad by English singer Adele, known for its emotive vocals and themes of nostalgia and regret.
- 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_69ca832c23e4819095a9f3eea4a21828 |
completed | March 30, 2026, 2:05 p.m. |
| NER | Named-entity recognition | batch_69cc46fc31e08190aab5ab8f92f3315c |
completed | March 31, 2026, 10:13 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69cea91456a88190a7416b0f1a0327d6 |
completed | April 2, 2026, 5:36 p.m. |
Created at: March 30, 2026, 6:25 p.m.