Triple
T32069240
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Rust-eze |
E818965
|
entity |
| Predicate | hasSpokescar |
P193610
|
FINISHED |
| Object | Lightning McQueen |
—
|
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: Lightning McQueen | Statement: [Rust-eze, hasSpokescar, Lightning McQueen]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasSpokescar Context triple: [Rust-eze, hasSpokescar, Lightning McQueen]
-
A.
hasSpokesmodel
Indicates that one entity serves as the official promotional representative or public face (spokesmodel) for another entity.
-
B.
hasSpeakerIn
Indicates that an event, work, or communication features a particular entity serving as its speaker.
-
C.
hasSpeakerType
Indicates that an entity functions in a particular role or category as a speaker (e.g., narrator, character, announcer) within a given context.
-
D.
hasNumberOfSpokes
Indicates the relationship that specifies how many spokes are present in or associated with an object.
-
E.
hasCarConstructor
Indicates that an entity is associated with a specific car constructor (manufacturer or builder) responsible for producing its car.
- 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_69f348fecc088190af1470afe5a969f0 |
completed | April 30, 2026, 12:20 p.m. |
| NER | Named-entity recognition | batch_69fd4d1854988190be093b103a681798 |
completed | May 8, 2026, 2:40 a.m. |
| PD | Predicate disambiguation | batch_69fd4c8d1a188190897c24527337814a |
completed | May 8, 2026, 2:38 a.m. |
| PDg | Predicate description generation | batch_69fd4d16dd20819096957c40f43cd971 |
completed | May 8, 2026, 2:40 a.m. |
Created at: May 1, 2026, 12:23 a.m.