Triple
T4322203
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | IRN-BRU Cup |
E96543
|
entity |
| Predicate | sponsorshipCategory |
P44270
|
FINISHED |
| Object | soft drink sponsorship |
—
|
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: soft drink sponsorship | Statement: [IRN-BRU Cup, sponsorshipCategory, soft drink sponsorship]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: sponsorshipCategory Context triple: [IRN-BRU Cup, sponsorshipCategory, soft drink sponsorship]
-
A.
sponsoringOrganizationType
Indicates the kind or category of organization that provides sponsorship or support in the described relationship or activity.
-
B.
sponsorshipScope
chosen
Indicates the extent, boundaries, or specific aspects of an activity, event, or entity that a sponsor’s support or involvement covers.
-
C.
sponsorshipName
Indicates the name or title associated with a sponsorship relationship between entities.
-
D.
sponsorType
Indicates the specific role or category of sponsorship that an entity provides in relation to another entity or event.
-
E.
sponsorEnd
Indicates the point in time or condition at which a sponsorship relationship or sponsorship-related action comes to an end.
- 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_69b345422aac81909ddbadae437d122e |
completed | March 12, 2026, 10:59 p.m. |
| NER | Named-entity recognition | batch_69b3511608dc8190afe912aa605ecace |
completed | March 12, 2026, 11:49 p.m. |
| PD | Predicate disambiguation | batch_69b34f4bec888190987fc2631498b637 |
completed | March 12, 2026, 11:42 p.m. |
Created at: March 12, 2026, 11:12 p.m.