Triple
T16806993
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Toyota Land Cruiser Prado J90 |
E408505
|
entity |
| Predicate | offRoadFeature |
P124921
|
FINISHED |
| Object | low-range transfer case |
—
|
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: low-range transfer case | Statement: [Toyota Land Cruiser Prado J90, offRoadFeature, low-range transfer case]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: offRoadFeature Context triple: [Toyota Land Cruiser Prado J90, offRoadFeature, low-range transfer case]
-
A.
hasOffRoadSections
Indicates that a route, path, or roadway includes segments that are not on standard paved or main roads, such as trails, dirt tracks, or other off-road portions.
-
B.
terrainCapability
Indicates the types of terrain or ground conditions in which an entity can effectively operate or function.
-
C.
offRoadBehavior
Indicates how an entity behaves, performs, or is operated when used off regular roads or standard paved surfaces.
-
D.
rideFeature
Indicates that one entity is a feature, characteristic, or component associated with a particular ride.
-
E.
trekkingFeature
Indicates a notable characteristic, condition, or element specifically associated with trekking activities or routes.
- F. None of above. chosen
Provenance (4 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_69d88393905081908d00a86b99996ac8 |
completed | April 10, 2026, 4:58 a.m. |
| NER | Named-entity recognition | batch_69e3b2cd1e8c8190a7a05ba255f711c7 |
completed | April 18, 2026, 4:35 p.m. |
| PD | Predicate disambiguation | batch_69e32b814b188190aee525f8779203cd |
completed | April 18, 2026, 6:58 a.m. |
| PDg | Predicate description generation | batch_69e34fb7c8c8819086975b7955b7d8ef |
completed | April 18, 2026, 9:32 a.m. |
Created at: April 10, 2026, 5:22 a.m.