Triple
T3929710
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Dusty Baker |
E93365
|
entity |
| Predicate | wonWorldSeriesAsManagerYear |
P21794
|
FINISHED |
| Object | 2022 |
—
|
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: 2022 | Statement: [Dusty Baker, wonWorldSeriesAsManagerYear, 2022]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: wonWorldSeriesAsManagerYear Context triple: [Dusty Baker, wonWorldSeriesAsManagerYear, 2022]
-
A.
worldSeriesChampionYearsAsManager
chosen
Indicates the years in which a person, acting as a manager, led a team to win the World Series championship.
-
B.
worldSeriesTitlesAsManager
Indicates the number of World Series championships an individual has won specifically in the role of a team manager.
-
C.
pennantsWonAsManager
Indicates the number of league pennants a person has won in their role as a team manager.
-
D.
wonAsManager
Indicates that one entity achieved a victory or title while serving in the role of manager of the other entity.
-
E.
managedInWorldSeries
Indicates that a person served as a manager for a team participating in a World Series.
- 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_69aed96bfa1081908f7b30f2c647dee6 |
completed | March 9, 2026, 2:30 p.m. |
| NER | Named-entity recognition | batch_69aeeda7cf3c81909df30744bddbad7e |
completed | March 9, 2026, 3:56 p.m. |
| PD | Predicate disambiguation | batch_69aee7609c4081908000ce12ae827c3f |
completed | March 9, 2026, 3:29 p.m. |
Created at: March 9, 2026, 3:23 p.m.