Triple
T36783343
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | New York Mets executive |
E908832
|
entity |
| Predicate | employerLeagueMembership |
P51847
|
FINISHED |
| Object | National League |
—
|
NE NERFINISHED |
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: National League | Statement: [New York Mets executive, employerLeagueMembership, National League]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: employerLeagueMembership Context triple: [New York Mets executive, employerLeagueMembership, National League]
-
A.
employerLeague
Indicates that an organization or entity serves as the employing league or governing competition body for another entity (such as a team or participant).
-
B.
affiliateLeague
Indicates that one sports organization or team is formally associated with and operates under the umbrella or partnership of a particular league.
-
C.
memberOfSportsLeague
chosen
Indicates that an entity is formally part of, or participates as a member in, a specific sports league.
-
D.
footballMembership
Indicates that an entity belongs to, is part of, or holds membership in a football-related organization, team, or group.
-
E.
tenantClubLeague
Indicates that a club participates as a tenant (home user of facilities) in a particular 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_69f76e7a937c81909ed7359641e670f6 |
completed | May 3, 2026, 3:49 p.m. |
| NER | Named-entity recognition | batch_69fccdd496048190bca801a8a9eecb62 |
completed | May 7, 2026, 5:37 p.m. |
| PD | Predicate disambiguation | batch_69fcccee6240819084680887731ff64b |
completed | May 7, 2026, 5:33 p.m. |
Created at: May 3, 2026, 4:12 p.m.