Triple
T9535881
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Joe McCarthy |
E230012
|
entity |
| Predicate | winLossRecordAsManager |
P18724
|
FINISHED |
| Object | 2125–1333 |
—
|
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: 2125–1333 | Statement: [Joe McCarthy, winLossRecordAsManager, 2125–1333]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: winLossRecordAsManager Context triple: [Joe McCarthy, winLossRecordAsManager, 2125–1333]
-
A.
careerWinLossRecord
chosen
Indicates the overall tally of wins and losses an entity has accumulated over the entire span of its career.
-
B.
wonAsManager
Indicates that one entity achieved a victory or title while serving in the role of manager of the other entity.
-
C.
pennantsWonAsManager
Indicates the number of league pennants a person has won in their role as a team manager.
-
D.
rankByManagerialWins
Indicates the ordering of entities based on the number of managerial wins they have achieved, from higher to lower (or vice versa) according to that metric.
-
E.
workedInLeagueAsManager
Indicates that a person has held a managerial role within a specific sports league.
- 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_69ca847b1b3081908f72bc932c17cc41 |
completed | March 30, 2026, 2:11 p.m. |
| NER | Named-entity recognition | batch_69cd98cd6a5c8190835c0910ec38ede3 |
completed | April 1, 2026, 10:14 p.m. |
| PD | Predicate disambiguation | batch_69cca56c44f88190a54a5d2a133bb07e |
completed | April 1, 2026, 4:56 a.m. |
Created at: March 30, 2026, 8 p.m.