Triple
T2625263
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Bob Paisley |
E59102
|
entity |
| Predicate | uefaCupsWonAsManager |
P31072
|
FINISHED |
| Object | 1 |
—
|
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: 1 | Statement: [Bob Paisley, uefaCupsWonAsManager, 1]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: uefaCupsWonAsManager Context triple: [Bob Paisley, uefaCupsWonAsManager, 1]
-
A.
hasWonDomesticCupsAsManager
Indicates that a person, in their role as a manager, has achieved victories in domestic cup competitions.
-
B.
wonAsManager
Indicates that one entity achieved a victory or title while serving in the role of manager of the other entity.
-
C.
wonChampionsLeagueAsPlayer
Indicates that the subject has been part of a team that won the UEFA Champions League in the role of a player.
-
D.
continentalTitleWonAsManager
chosen
Indicates that the person has won a continental-level competition title in the role of a manager.
-
E.
UEFAChampionsLeagueTitles
Indicates the number of UEFA Champions League titles an entity (typically a football club) has won.
- 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_69ab4ac558388190962492cd2e1b0ce6 |
completed | March 6, 2026, 9:44 p.m. |
| NER | Named-entity recognition | batch_69abdaca581881908fe8d3d820f839b7 |
completed | March 7, 2026, 7:59 a.m. |
| PD | Predicate disambiguation | batch_69abd80f48888190afdf7e3e042157d0 |
completed | March 7, 2026, 7:47 a.m. |
Created at: March 6, 2026, 9:50 p.m.