Triple
T29190378
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Sebulba |
E739973
|
entity |
| Predicate | podracerModel |
P131602
|
FINISHED |
| Object | IPG-X1131 LongTail podracer |
—
|
NE NERFINISHED |
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: IPG-X1131 LongTail podracer | Statement: [Sebulba, podracerModel, IPG-X1131 LongTail podracer]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: podracerModel Context triple: [Sebulba, podracerModel, IPG-X1131 LongTail podracer]
-
A.
rideModel
Indicates that one entity is a specific model or type designation of a ride associated with another entity.
-
B.
hasFictionalVehicle
chosen
Indicates that one entity possesses, controls, or is associated with a vehicle that exists only in a fictional or imaginary context.
-
C.
rocketVariant
Indicates a specific version or configuration of a given rocket.
-
D.
notableCoasterModel
Indicates that a roller coaster is an especially prominent or significant example of a particular coaster model or design.
-
E.
producedVehicle
Indicates that one entity manufactured or created a particular vehicle.
- 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_69f07cb8033c8190b8807e219a14333d |
completed | April 28, 2026, 9:24 a.m. |
| NER | Named-entity recognition | batch_69f6638aa68c8190a02fd50ecd5a96fd |
completed | May 2, 2026, 8:50 p.m. |
| PD | Predicate disambiguation | batch_69f65c24f8b48190af81b575f3c15be5 |
completed | May 2, 2026, 8:18 p.m. |
Created at: April 28, 2026, 12:02 p.m.