Triple
T589376
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | George Steinbrenner |
E17232
|
entity |
| Predicate | teamPennantsUnderOwnership |
P892
|
FINISHED |
| Object | 11 American League pennants |
—
|
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: 11 American League pennants | Statement: [George Steinbrenner, teamPennantsUnderOwnership, 11 American League pennants]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: teamPennantsUnderOwnership Context triple: [George Steinbrenner, teamPennantsUnderOwnership, 11 American League pennants]
-
A.
leaguePennants
chosen
Indicates that a team has won a specified number of league pennants (championship titles) in a particular league.
-
B.
mostPennantsTeam
Indicates that the subject is the team that has won the greatest number of league pennants within a specified context or league.
-
C.
pennantTeam
Indicates that a team has won or represents the league or conference pennant for a given season or competition.
-
D.
leaguePennant
Indicates that a team has won the championship pennant for a particular league or season.
-
E.
previousTeamNamesAlsoAssociatedWithFranchise
Indicates that the earlier team names are also historically or officially linked to the same franchise.
- 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_69a49379d09c8190ac7e00b24e2810b1 |
completed | March 1, 2026, 7:28 p.m. |
| NER | Named-entity recognition | batch_69a49bb775fc819085b968f8615dca59 |
completed | March 1, 2026, 8:04 p.m. |
| PD | Predicate disambiguation | batch_69a494cc13988190892ca10bd7ae9f09 |
completed | March 1, 2026, 7:34 p.m. |
Created at: March 1, 2026, 7:33 p.m.