Triple
T13228120
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Jaguar XE |
E314933
|
entity |
| Predicate | manufacturer |
P490
|
FINISHED |
| Object | Jaguar Cars |
E316566
|
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: Jaguar Cars | Statement: [Jaguar XE, manufacturer, Jaguar Cars]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Jaguar Cars Context triple: [Jaguar XE, manufacturer, Jaguar Cars]
-
A.
Jaguar Land Rover
chosen
Jaguar Land Rover is a British multinational automotive company known for designing and manufacturing luxury vehicles under the Jaguar and Land Rover brands.
-
B.
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.
-
C.
Lotus Cars
Lotus Cars is a British sports car manufacturer renowned for its lightweight, high-performance vehicles and engineering innovation.
-
D.
Bentley
Bentley is a small village and civil parish in Suffolk, England, known for its rural character and traditional English countryside setting.
-
E.
Bentley
Bentley is a small rural village and civil parish in East Hampshire, England, known for its countryside setting and traditional English character.
- 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_69d806affc688190a25b6ccc588e9c72 |
completed | April 9, 2026, 8:06 p.m. |
| NER | Named-entity recognition | batch_69d98d3232d48190a3c792b025c596a6 |
completed | April 10, 2026, 11:52 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69f6ff2a4b0c8190a853a1f6f4d1cbaf |
completed | May 3, 2026, 7:54 a.m. |
Created at: April 9, 2026, 9:21 p.m.