Triple
T267250
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | UEFA |
E5757
|
entity |
| Predicate | presidentSince |
P8942
|
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: [UEFA, presidentSince, 2016]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: presidentSince Context triple: [UEFA, presidentSince, 2016]
-
A.
inauguratedBy
Indicates that an official event, institution, or position was formally opened, initiated, or brought into operation by a specific person or authority.
-
B.
hasPresident
Indicates that an entity holds the position or role of president for another entity.
-
C.
presidentInaugurated
Indicates that an individual formally assumes the office of president through an official inauguration event at a specific time and place.
-
D.
inaugurationYear
Indicates the calendar year in which an entity was formally inaugurated or officially brought into operation.
-
E.
lastPresident
Indicates that one entity is the most recent individual to have held the office of president of the other entity.
- 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_69a2587daeb081909591b9d30f80a271 |
completed | Feb. 28, 2026, 2:52 a.m. |
| NER | Named-entity recognition | batch_69a25dacf60c8190a5c3ef455b9a8b20 |
completed | Feb. 28, 2026, 3:14 a.m. |
| PD | Predicate disambiguation | batch_69a25b6f60b081908fc6467800a8849e |
completed | Feb. 28, 2026, 3:05 a.m. |
| PDg | Predicate description generation | batch_69a25c8ae480819094f6d1bb0a6d2eb2 |
completed | Feb. 28, 2026, 3:10 a.m. |
Created at: Feb. 28, 2026, 2:56 a.m.