Triple
T20826821
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | 1962 World Series |
E512723
|
entity |
| Predicate | YankeesPennantCountToDate |
P141972
|
FINISHED |
| Object | 27 |
—
|
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: 27 | Statement: [1962 World Series, YankeesPennantCountToDate, 27]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: YankeesPennantCountToDate Context triple: [1962 World Series, YankeesPennantCountToDate, 27]
-
A.
YankeesGamesWon
Indicates the number of games that the New York Yankees have won.
-
B.
YankeesConsecutiveTitles
Indicates that the New York Yankees won championship titles in consecutive seasons.
-
C.
numberOfTimesManagedNewYorkYankees
Indicates how many separate times an individual has served as the manager of the New York Yankees.
-
D.
YankeesPreviousTitle
Indicates that the subject entity is the immediately preceding championship title held by the New York Yankees before the object entity.
-
E.
YankeesTeamEarnedRunAverage
Indicates the average number of earned runs allowed per nine innings by the Yankees team over a specified period.
- F. None of above. chosen
Provenance (4 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_69e0b4ce39108190a6e8e5df4f1c8dc5 |
completed | April 16, 2026, 10:07 a.m. |
| NER | Named-entity recognition | batch_69e6c2fe54608190a061274bf4316610 |
completed | April 21, 2026, 12:21 a.m. |
| PD | Predicate disambiguation | batch_69e5c9a1f4f48190aa9fb4ef8f8aea5a |
completed | April 20, 2026, 6:37 a.m. |
| PDg | Predicate description generation | batch_69e5d53c4d6881909b4d0a716fa5ed4a |
completed | April 20, 2026, 7:26 a.m. |
Created at: April 16, 2026, 12:41 p.m.