Triple
T2625264
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Bob Paisley |
E59102
|
entity |
| Predicate | leagueCupsWonAsManager |
P31074
|
FINISHED |
| Object | 3 |
—
|
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: 3 | Statement: [Bob Paisley, leagueCupsWonAsManager, 3]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: leagueCupsWonAsManager Context triple: [Bob Paisley, leagueCupsWonAsManager, 3]
-
A.
hasWonDomesticCupsAsManager
chosen
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.
continentalTitleWonAsManager
Indicates that the person has won a continental-level competition title in the role of a manager.
-
D.
championshipWonAsCoach
Indicates that the subject, acting in the role of coach, has won a championship title with the associated team or organization.
-
E.
pennantsWonAsManager
Indicates the number of league pennants a person has won in their role as a team manager.
- 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.