Triple
T32424759
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Japanese Grand Prix |
E828547
|
entity |
| Predicate | hasTitleSponsorInVariousYears |
P55710
|
FINISHED |
| Object | Honda |
—
|
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: Honda | Statement: [Japanese Grand Prix, hasTitleSponsorInVariousYears, Honda]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasTitleSponsorInVariousYears Context triple: [Japanese Grand Prix, hasTitleSponsorInVariousYears, Honda]
-
A.
hasTitleSponsorHistorically
chosen
Indicates that an entity has served as the primary (title) sponsor of another entity during some period in the past.
-
B.
hasTitleSponsor
Indicates that one entity serves as the primary (title) sponsor for another entity, typically giving its name to the sponsored event, organization, or property.
-
C.
sponsorshipEra
Indicates the time period during which a sponsorship relationship is in effect between parties.
-
D.
hasSponsorSinceInauguration
Indicates that an entity has continuously had the same sponsor from the time of its inauguration or start date onward.
-
E.
sponsorshipNameSince
Indicates the date or time from which a particular sponsorship name has been in effect for the associated entity or relationship.
- 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_69f3491b28bc8190b75cea7a507f337b |
completed | April 30, 2026, 12:20 p.m. |
| NER | Named-entity recognition | batch_69fd32848ea88190a71e6df402bbb30e |
completed | May 8, 2026, 12:47 a.m. |
| PD | Predicate disambiguation | batch_69fd2d7e95588190991d5f21e25155df |
completed | May 8, 2026, 12:25 a.m. |
Created at: May 1, 2026, 12:54 a.m.