Triple
T14580379
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | George Lee Anderson |
E342175
|
entity |
| Predicate | careerManagerialWinningPercentage |
P88592
|
FINISHED |
| Object | .545 |
—
|
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: .545 | Statement: [George Lee Anderson, careerManagerialWinningPercentage, .545]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: careerManagerialWinningPercentage Context triple: [George Lee Anderson, careerManagerialWinningPercentage, .545]
-
A.
careerManagerialWins
Indicates the total number of games or contests an individual has won in a managerial role over the course of their entire career.
-
B.
winningPercentageAsManager
chosen
Indicates the proportion of games a person has won while serving in the role of manager.
-
C.
careerWins
Indicates the total number of wins an individual or entity has accumulated over the course of their entire career.
-
D.
careerWinLossRecord
Indicates the overall tally of wins and losses an entity has accumulated over the entire span of its career.
-
E.
allTimeWinningPercentage
Indicates the proportion of contests or games an entity has won over its entire recorded history, typically expressed as a percentage.
- 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_69d822ddc0f081909cd8163c7de298cd |
completed | April 9, 2026, 10:06 p.m. |
| NER | Named-entity recognition | batch_69deb3f6f78c81908a30ecb4c025299d |
completed | April 14, 2026, 9:39 p.m. |
| PD | Predicate disambiguation | batch_69de656a953481909a4645b004c40de7 |
completed | April 14, 2026, 4:03 p.m. |
Created at: April 10, 2026, 1:24 a.m.