Triple
T34602708
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | O2 Forum Kentish Town |
E888509
|
entity |
| Predicate | sponsorshipBrandingSince |
P179684
|
FINISHED |
| Object | 2008 |
—
|
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: 2008 | Statement: [O2 Forum Kentish Town, sponsorshipBrandingSince, 2008]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: sponsorshipBrandingSince Context triple: [O2 Forum Kentish Town, sponsorshipBrandingSince, 2008]
-
A.
sponsorshipBrand
Indicates that one entity serves as a sponsoring brand for another entity, typically providing support, funding, or endorsement.
-
B.
sponsorBrandType
Indicates the type or category of brand that is acting as a sponsor in the relationship.
-
C.
sponsorshipRenamedFrom
Indicates that a sponsorship currently known by one name previously existed under a different, earlier name.
-
D.
sponsorshipName
Indicates the name or title associated with a sponsorship relationship between entities.
-
E.
sharesBrandingWith
Indicates that two entities use the same or closely related branding elements, such as name, logo, or visual identity.
- 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_69f349d489d48190ba30e7d97c6f5ef9 |
completed | April 30, 2026, 12:23 p.m. |
| NER | Named-entity recognition | batch_69f7238172748190b8cd340ad1f4ba80 |
completed | May 3, 2026, 10:29 a.m. |
| PD | Predicate disambiguation | batch_69f72155c48881909bd40b9aa3febd5a |
completed | May 3, 2026, 10:20 a.m. |
| PDg | Predicate description generation | batch_69f72349f1108190b6a06758ab2f40bb |
completed | May 3, 2026, 10:28 a.m. |
Created at: May 1, 2026, 2:03 a.m.