Triple
T4351957
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | AFC Champions League |
E98045
|
entity |
| Predicate | hasTitleSponsorHistorically |
P55710
|
FINISHED |
| Object | yes |
—
|
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: yes | Statement: [AFC Champions League, hasTitleSponsorHistorically, yes]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasTitleSponsorHistorically Context triple: [AFC Champions League, hasTitleSponsorHistorically, yes]
-
A.
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.
-
B.
sponsorshipEra
Indicates the time period during which a sponsorship relationship is in effect between parties.
-
C.
sponsorshipNameSince
Indicates the date or time from which a particular sponsorship name has been in effect for the associated entity or relationship.
-
D.
hasSponsor
Indicates that one entity financially or otherwise supports another entity, typically in exchange for recognition or other benefits.
-
E.
previousSponsorshipName
Indicates that an entity had a different sponsorship name in the past, specifying what that prior sponsored name was.
- 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_69b3454965f881908c41190bb22f0e4b |
completed | March 12, 2026, 10:59 p.m. |
| NER | Named-entity recognition | batch_69b351ab03488190a8900de98fb4a00e |
completed | March 12, 2026, 11:52 p.m. |
| PD | Predicate disambiguation | batch_69b34f51ed7c8190b7bf5f44b56b730d |
completed | March 12, 2026, 11:42 p.m. |
| PDg | Predicate description generation | batch_69b34ff654308190b9717526120d80d3 |
completed | March 12, 2026, 11:44 p.m. |
Created at: March 12, 2026, 11:15 p.m.