Triple
T5695372
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Chuck Tanner |
E125525
|
entity |
| Predicate | managerialWinLossRecord |
P18724
|
FINISHED |
| Object | 1352–1381 |
—
|
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: 1352–1381 | Statement: [Chuck Tanner, managerialWinLossRecord, 1352–1381]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: managerialWinLossRecord Context triple: [Chuck Tanner, managerialWinLossRecord, 1352–1381]
-
A.
careerWinLossRecord
chosen
Indicates the overall tally of wins and losses an entity has accumulated over the entire span of its career.
-
B.
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.
-
C.
managerialWinsMLB
Indicates that the subject has achieved a specified number of wins as a manager in Major League Baseball.
-
D.
winningManagerTeam
Indicates that the specified manager is the head coach/manager of the team that won a particular game, match, or competition.
-
E.
seasonRecord
Indicates the overall performance or results an entity achieved over the course of a specific season (e.g., wins, losses, or comparable outcome metrics).
- 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_69c0082bb19c8190823a4facd3cba79b |
completed | March 22, 2026, 3:18 p.m. |
| NER | Named-entity recognition | batch_69c029014588819094a2a0f6f9b66bab |
completed | March 22, 2026, 5:38 p.m. |
| PD | Predicate disambiguation | batch_69c021c0e0408190ab6c3cd3f907e80f |
completed | March 22, 2026, 5:07 p.m. |
Created at: March 22, 2026, 3:45 p.m.