Triple
T13269609
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Frankie Crosetti |
E316019
|
entity |
| Predicate | numberOfWorldSeriesTitlesAsCoach |
P109236
|
FINISHED |
| Object | 9 |
—
|
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: 9 | Statement: [Frankie Crosetti, numberOfWorldSeriesTitlesAsCoach, 9]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: numberOfWorldSeriesTitlesAsCoach Context triple: [Frankie Crosetti, numberOfWorldSeriesTitlesAsCoach, 9]
-
A.
wonWorldSeriesAsCoachWith
Indicates that one entity served as a coach for a team that won the World Series together with the other entity.
-
B.
numberOfWorldChampionsCoached
Indicates the count of distinct world champion individuals that a given coach has trained.
-
C.
worldSeriesTitlesAsManager
Indicates the number of World Series championships an individual has won specifically in the role of a team 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.
numberOfStanleyCupsAsCoachOrExecutive
Indicates the total count of Stanley Cup championships an individual has won specifically in the roles of coach or executive.
- 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_69d806b1d9ac8190852c5571d5bd5f0f |
completed | April 9, 2026, 8:06 p.m. |
| NER | Named-entity recognition | batch_69d99cfdc9388190af1fdd3cd4717bd8 |
completed | April 11, 2026, 12:59 a.m. |
| PD | Predicate disambiguation | batch_69d98f60911081909fa346a054f76c9f |
completed | April 11, 2026, 12:01 a.m. |
| PDg | Predicate description generation | batch_69d99cf7f9c48190a6a4f452b4a2aefa |
completed | April 11, 2026, 12:59 a.m. |
Created at: April 9, 2026, 9:26 p.m.