Triple
T37227590
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | The Ant Hill Mob |
E923044
|
entity |
| Predicate | associatedVehicleFeature |
P67070
|
FINISHED |
| Object | car is heavily armored |
—
|
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: car is heavily armored | Statement: [The Ant Hill Mob, associatedVehicleFeature, car is heavily armored]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: associatedVehicleFeature Context triple: [The Ant Hill Mob, associatedVehicleFeature, car is heavily armored]
-
A.
featuresVehicle
Indicates that one entity includes, presents, or prominently incorporates a particular vehicle as part of its content, composition, or offering.
-
B.
hasVehicleFeature
chosen
Indicates that a vehicle possesses, includes, or is equipped with a specific feature or characteristic.
-
C.
chassisFeature
Indicates that a particular feature, component, or characteristic is part of or associated with a chassis.
-
D.
usesVehicleVariant
Indicates that one entity performs an action or function by employing a specific variant or version of a vehicle.
-
E.
basedOnVehicle
Indicates that one entity is derived from, modeled after, or otherwise conceptually or functionally based on 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_69f76ea7f0008190b31b8e30f3d05a71 |
completed | May 3, 2026, 3:50 p.m. |
| NER | Named-entity recognition | batch_6a037c8efcd4819088c2aeead65d93df |
completed | May 12, 2026, 7:16 p.m. |
| PD | Predicate disambiguation | batch_6a037a11efc08190bb7cacc1325b4dc6 |
completed | May 12, 2026, 7:05 p.m. |
Created at: May 3, 2026, 4:15 p.m.