Triple
T586002
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Leeds United F.C. |
E15157
|
entity |
| Predicate | shirtSponsorHistory |
P15097
|
FINISHED |
| Object | various commercial sponsors |
—
|
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: various commercial sponsors | Statement: [Leeds United F.C., shirtSponsorHistory, various commercial sponsors]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: shirtSponsorHistory Context triple: [Leeds United F.C., shirtSponsorHistory, various commercial sponsors]
-
A.
previousSponsorshipName
Indicates that an entity had a different sponsorship name in the past, specifying what that prior sponsored name was.
-
B.
previousTeamNamesAlsoAssociatedWithFranchise
Indicates that the earlier team names are also historically or officially linked to the same franchise.
-
C.
hasInsigniaWornBy
Indicates that a particular insignia is worn by a specified entity (such as a person, group, or organization).
-
D.
sportsBrand
Indicates that one entity is a sports-related brand or label associated with the other entity.
-
E.
sponsorshipName
chosen
Indicates the name or title associated with a sponsorship relationship between entities.
- 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_69a4935783b8819082b77726ec10cc42 |
completed | March 1, 2026, 7:28 p.m. |
| NER | Named-entity recognition | batch_69a49b9a46388190a094b9ebf8dec397 |
completed | March 1, 2026, 8:03 p.m. |
| PD | Predicate disambiguation | batch_69a494ca68448190a516b9c3525d8916 |
completed | March 1, 2026, 7:34 p.m. |
Created at: March 1, 2026, 7:33 p.m.