Triple
T31572276
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | George Pipgras |
E805596
|
entity |
| Predicate | umpireCareerStartYear |
P128323
|
FINISHED |
| Object | 1938 |
—
|
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: 1938 | Statement: [George Pipgras, umpireCareerStartYear, 1938]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: umpireCareerStartYear Context triple: [George Pipgras, umpireCareerStartYear, 1938]
-
A.
umpireDebutYear
Indicates the year in which an individual first began serving as an umpire, typically in an official or professional capacity.
-
B.
umpiringCareerStartYear
chosen
Indicates the calendar year in which an individual began their career as an umpire.
-
C.
yearsActiveAsUmpire
Indicates the span of time during which an entity has served or been active in the role of an umpire.
-
D.
playedCareerStartYear
Indicates the calendar year in which an entity’s playing career (such as a professional or competitive role) began.
-
E.
umpiresProvidedBy
Indicates that one entity supplies or assigns umpires to officiate for another entity or event.
- 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_69f348d2ee94819091918d1789398c29 |
completed | April 30, 2026, 12:19 p.m. |
| NER | Named-entity recognition | batch_69f6a8055f8081908f635fe04654b5fe |
completed | May 3, 2026, 1:42 a.m. |
| PD | Predicate disambiguation | batch_69f6a75656e081908739ed9e2f600e42 |
completed | May 3, 2026, 1:39 a.m. |
Created at: April 30, 2026, 10:20 p.m.