Triple
T1095272
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Mike Scioscia |
E24256
|
entity |
| Predicate | WorldSeriesTitlesAsManager |
P11323
|
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: [Mike Scioscia, WorldSeriesTitlesAsManager, 1]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: WorldSeriesTitlesAsManager Context triple: [Mike Scioscia, WorldSeriesTitlesAsManager, 1]
-
A.
worldSeriesTitlesAsManager
chosen
Indicates the number of World Series championships an individual has won specifically in the role of a team manager.
-
B.
worldSeriesChampionYearsAsManager
Indicates the years in which a person, acting as a manager, led a team to win the World Series championship.
-
C.
worldSeriesTitles
Indicates the number of World Series championship titles an entity (typically a baseball team) has won.
-
D.
pennantsWonAsManager
Indicates the number of league pennants a person has won in their role as a team manager.
-
E.
numberOfWorldSeriesTitles
Indicates the count of World Series championship titles that an entity (typically a baseball team or player) 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_69a4940542308190ac2a0b1f730b7cfc |
completed | March 1, 2026, 7:31 p.m. |
| NER | Named-entity recognition | batch_69a4b99e92308190b8a8c499e1630672 |
completed | March 1, 2026, 10:11 p.m. |
| PD | Predicate disambiguation | batch_69a4b743175481908f3967e589717c55 |
completed | March 1, 2026, 10:01 p.m. |
Created at: March 1, 2026, 7:42 p.m.