Triple
T32672557
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Maggie Peyton |
E835335
|
entity |
| Predicate | hasSentientCarPartner |
P1136
|
FINISHED |
| Object | Herbie |
—
|
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: Herbie | Statement: [Maggie Peyton, hasSentientCarPartner, Herbie]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasSentientCarPartner Context triple: [Maggie Peyton, hasSentientCarPartner, Herbie]
-
A.
hasChassisPartner
Indicates that one entity is partnered or associated with another specifically for sharing or collaborating on a chassis design or platform.
-
B.
hasEnginePartner
Indicates a relationship where one engine is paired or associated with another engine as its partner in operation or configuration.
-
C.
hasPartner
chosen
Indicates that one entity is in a partner relationship (such as romantic, life, or business partnership) with another entity.
-
D.
hasSignatureCar
Indicates that an entity is associated with a distinctive or characteristic car that is uniquely identified with it.
-
E.
hasAutonomousDrivingHardware
Indicates that an entity is equipped with hardware components that enable or support autonomous driving capabilities.
- 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_69f3493134b48190aa3c8cb523bd3800 |
completed | April 30, 2026, 12:21 p.m. |
| NER | Named-entity recognition | batch_69ff5b233e9c8190adc06cca0758986b |
completed | May 9, 2026, 4:04 p.m. |
| PD | Predicate disambiguation | batch_69ff5a5682108190a006b23c4fcdcc7c |
completed | May 9, 2026, 4:01 p.m. |
Created at: May 1, 2026, 1:09 a.m.