Triple
T13668090
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Sam Tyler |
E327673
|
entity |
| Predicate | vehicleOfTimeDisplacement |
P111076
|
FINISHED |
| Object | car accident in 2006 |
—
|
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 accident in 2006 | Statement: [Sam Tyler, vehicleOfTimeDisplacement, car accident in 2006]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: vehicleOfTimeDisplacement Context triple: [Sam Tyler, vehicleOfTimeDisplacement, car accident in 2006]
-
A.
vehicleDeveloped
Indicates that an entity (such as a person, organization, or group) created, designed, or otherwise developed a particular vehicle.
-
B.
starVehicleFor
Indicates that one entity serves as the primary or featured vehicle associated with another entity, such as a person, production, or event.
-
C.
reentryVehicle
Indicates that an entity functions as a vehicle designed to re-enter an atmosphere from space.
-
D.
mechanicalTransport
Indicates a relationship where an entity is moved or carried from one place to another using a mechanical means of transportation (e.g., vehicles, machines, or devices).
-
E.
intendedCrewVehicle
Indicates that a particular vehicle is designated or planned to be used by a specific crew.
- 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_69d8076f1fa8819094664a59b55010df |
completed | April 9, 2026, 8:09 p.m. |
| NER | Named-entity recognition | batch_69dbc65832688190aea688fee0a7cbdb |
completed | April 12, 2026, 4:20 p.m. |
| PD | Predicate disambiguation | batch_69dbbe8d8d0881908d6e89954f44eed4 |
completed | April 12, 2026, 3:47 p.m. |
| PDg | Predicate description generation | batch_69dbc59ca1a88190a6abd3bd00554c93 |
completed | April 12, 2026, 4:17 p.m. |
Created at: April 9, 2026, 9:52 p.m.