Triple
T15731559
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | George Brett |
E381356
|
entity |
| Predicate | playedEntireCareerForOneTeam |
P14859
|
FINISHED |
| Object | yes |
—
|
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: yes | Statement: [George Brett, playedEntireCareerForOneTeam, yes]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: playedEntireCareerForOneTeam Context triple: [George Brett, playedEntireCareerForOneTeam, yes]
-
A.
playedEntireCareerForSingleFranchise
Indicates that an athlete spent their entire professional career playing for only one franchise or team.
-
B.
spentEntireMLBCareerWith
chosen
Indicates that a player spent their entire Major League Baseball career with a single team.
-
C.
teamPlayedFor
Indicates that a person was a member of and played for a particular sports team.
-
D.
playedFor
Indicates that one entity has been a member of or participated as a player for a particular team, organization, or group.
-
E.
positionPlayedForTeam
Indicates the specific playing position or role an individual held while participating on a particular team.
- 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_69d86d9cdb648190bf3171be0bd7d872 |
completed | April 10, 2026, 3:25 a.m. |
| NER | Named-entity recognition | batch_69e04fb61cb881908b158609c1ccfa1e |
completed | April 16, 2026, 2:55 a.m. |
| PD | Predicate disambiguation | batch_69e00526759c819088b80d85138b8974 |
completed | April 15, 2026, 9:37 p.m. |
Created at: April 10, 2026, 4:46 a.m.