Triple
T17162526
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Citroën Xantia |
E416515
|
entity |
| Predicate | designer |
P184
|
FINISHED |
| Object | Bertone |
E398808
|
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: Bertone | Statement: [Citroën Xantia, designer, Bertone]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Bertone Context triple: [Citroën Xantia, designer, Bertone]
-
A.
Bertone
chosen
Bertone is an Italian automotive design and coachbuilding firm renowned for styling numerous iconic European cars.
-
B.
Bertone
Bertone is an Italian surname most notably associated with Tarcisio Bertone, a prominent cardinal and former Vatican Secretary of State.
-
C.
Zagato
Zagato is an Italian automotive design and coachbuilding firm renowned for its lightweight, aerodynamically styled sports and racing cars.
-
D.
Carrozzeria Ghia
Carrozzeria Ghia is an Italian automotive design and coachbuilding firm renowned for its stylish mid-20th-century car designs for various major manufacturers.
-
E.
Italdesign
Italdesign is an Italian automotive design and engineering firm renowned for creating iconic car designs for major manufacturers worldwide.
- 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_69d886d279c081909f8ff1f743ddeb69 |
completed | April 10, 2026, 5:12 a.m. |
| NER | Named-entity recognition | batch_69e3f91316108190b0d856d6fa5cd509 |
completed | April 18, 2026, 9:35 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_6a01483969a48190a90268c9560b8cd7 |
completed | May 11, 2026, 3:08 a.m. |
Created at: April 10, 2026, 5:37 a.m.