Triple
T1323006
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Baojun RC-6 |
E28261
|
entity |
| Predicate | hasInfotainmentSystem |
P6655
|
FINISHED |
| Object | large central touchscreen |
—
|
LITERAL 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: large central touchscreen | Statement: [Baojun RC-6, hasInfotainmentSystem, large central touchscreen]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasInfotainmentSystem Context triple: [Baojun RC-6, hasInfotainmentSystem, large central touchscreen]
-
A.
hasPassengerInformationSystem
Indicates that an entity is equipped with a system that provides information to passengers, such as schedules, announcements, or travel updates.
-
B.
hasOnboardComputer
Indicates that one entity is equipped with or contains an onboard computer system.
-
C.
hasOnboardSystems
Indicates that an entity is equipped with or contains specific onboard systems or subsystems.
-
D.
hasInteriorFeature
chosen
Indicates that an entity contains or includes a specific feature within its interior space.
-
E.
featuresVehicle
Indicates that one entity includes, presents, or prominently incorporates a particular vehicle as part of its content, composition, or offering.
- F. None of above.
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_69a498540a2481909e807a762280d3ba |
completed | March 1, 2026, 7:49 p.m. |
| NER | Named-entity recognition | batch_69a4c19b76b48190aa8857b80971a842 |
completed | March 1, 2026, 10:45 p.m. |
| PD | Predicate disambiguation | batch_69a4beedb49c8190beb5b85cdda05013 |
completed | March 1, 2026, 10:34 p.m. |
Created at: March 1, 2026, 7:55 p.m.