Triple
T15662644
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Beazley Designs of the Year |
E376603
|
entity |
| Predicate | renamedAfterSponsorship |
P119655
|
FINISHED |
| Object | 2016 |
—
|
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: 2016 | Statement: [Beazley Designs of the Year, renamedAfterSponsorship, 2016]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: renamedAfterSponsorship Context triple: [Beazley Designs of the Year, renamedAfterSponsorship, 2016]
-
A.
renamingSponsor
Indicates that one entity serves as the sponsor responsible for the renaming of another entity.
-
B.
sponsorshipRenamedFrom
Indicates that a sponsorship currently known by one name previously existed under a different, earlier name.
-
C.
sponsorshipChangeTo
Indicates a change in sponsorship where an entity becomes the new sponsor of another entity, replacing or updating the previous sponsorship arrangement.
-
D.
previousSponsorshipName
Indicates that an entity had a different sponsorship name in the past, specifying what that prior sponsored name was.
-
E.
sponsorshipNameAdopted
Indicates that an entity has adopted or taken on a specific sponsorship name as its official or recognized designation.
- 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_69d85cd1564c8190991adda63bfab4b0 |
completed | April 10, 2026, 2:13 a.m. |
| NER | Named-entity recognition | batch_69e04f0e2668819092e52712cddd0721 |
completed | April 16, 2026, 2:53 a.m. |
| PD | Predicate disambiguation | batch_69deda8b36a4819081cb5708fe77ef51 |
completed | April 15, 2026, 12:23 a.m. |
| PDg | Predicate description generation | batch_69dff7f3016c8190ac68d76e65e07af4 |
completed | April 15, 2026, 8:41 p.m. |
Created at: April 10, 2026, 4:15 a.m.