Triple
T11760903
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | LaserDisc |
E279651
|
entity |
| Predicate | CAVFeature |
P101229
|
FINISHED |
| Object | perfect still frame |
—
|
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: perfect still frame | Statement: [LaserDisc, CAVFeature, perfect still frame]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: CAVFeature Context triple: [LaserDisc, CAVFeature, perfect still frame]
-
A.
hasVehicleFeature
Indicates that a vehicle possesses, includes, or is equipped with a specific feature or characteristic.
-
B.
hasTrafficFeature
Indicates that an entity possesses or is associated with a specific traffic-related characteristic, element, or infrastructure feature.
-
C.
driveAssistFeature
Indicates that one entity provides an assistance feature that helps another entity perform driving-related tasks.
-
D.
featuresVehicle
Indicates that one entity includes, presents, or prominently incorporates a particular vehicle as part of its content, composition, or offering.
-
E.
transportCharacteristic
Indicates a relationship where a specific characteristic, property, or feature is attributed to a mode or instance of transport.
- 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_69d6ab01038c819080714901502c84fc |
completed | April 8, 2026, 7:22 p.m. |
| NER | Named-entity recognition | batch_69d8a52386708190b744746a2db37495 |
completed | April 10, 2026, 7:22 a.m. |
| PD | Predicate disambiguation | batch_69d88a829fe481909cc5431de7d6058e |
completed | April 10, 2026, 5:28 a.m. |
| PDg | Predicate description generation | batch_69d890467a2481909ce6c669e739c8de |
completed | April 10, 2026, 5:53 a.m. |
Created at: April 8, 2026, 9:41 p.m.