Triple
T7182574
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Danny Murtaugh |
E167483
|
entity |
| Predicate | managerialWinningPercentage |
P44736
|
FINISHED |
| Object | .540 |
—
|
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: .540 | Statement: [Danny Murtaugh, managerialWinningPercentage, .540]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: managerialWinningPercentage Context triple: [Danny Murtaugh, managerialWinningPercentage, .540]
-
A.
allTimeWinningPercentage
Indicates the proportion of contests or games an entity has won over its entire recorded history, typically expressed as a percentage.
-
B.
winningPercentageAsHeadCoach
chosen
Indicates the proportion of games a person has won while serving in the role of head coach.
-
C.
managerialWinsMLB
Indicates that the subject has achieved a specified number of wins as a manager in Major League Baseball.
-
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.
championshipWinRate
Indicates the proportion of championships won relative to the total number of championship opportunities or appearances.
- 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_69c6888a7c548190a3d39b52a393080f |
completed | March 27, 2026, 1:39 p.m. |
| NER | Named-entity recognition | batch_69c6e9b045c48190b27b2d6f7c11026f |
completed | March 27, 2026, 8:33 p.m. |
| PD | Predicate disambiguation | batch_69c6e74fb0f48190b2ad4dd4efdd241a |
completed | March 27, 2026, 8:23 p.m. |
Created at: March 27, 2026, 2:49 p.m.