Triple
T5755763
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Rolls-Royce Motors |
E126961
|
entity |
| Predicate | brand |
P1500
|
FINISHED |
| Object | Bentley |
E38523
|
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: Bentley | Statement: [Rolls-Royce Motors, brand, Bentley]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Bentley Context triple: [Rolls-Royce Motors, brand, Bentley]
-
A.
Bentley
chosen
Bentley is a British luxury automobile manufacturer renowned for its high-performance grand tourers and handcrafted interiors.
-
B.
Bentley
Bentley is a small village and civil parish in Suffolk, England, known for its rural character and traditional English countryside setting.
-
C.
Bentley
Bentley is a small rural village and civil parish in East Hampshire, England, known for its countryside setting and traditional English character.
-
D.
Aston Martin
Aston Martin is a British luxury sports car manufacturer renowned for its high-performance grand tourers and long association with the James Bond film franchise.
-
E.
Bentley Mulliner
Bentley Mulliner is Bentley Motors’ bespoke coachbuilding and customization division, renowned for creating highly personalized, ultra-luxury versions of the brand’s cars.
- 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_69c00832aedc81909899801b141fa3b4 |
completed | March 22, 2026, 3:18 p.m. |
| NER | Named-entity recognition | batch_69c02906848c8190bf7b0d62f57c27fa |
completed | March 22, 2026, 5:38 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69c0a16b9eac8190a3760557e2aebb45 |
completed | March 23, 2026, 2:11 a.m. |
Created at: March 22, 2026, 3:49 p.m.