Triple
T5650036
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | John Byron Nelson Jr. |
E124479
|
entity |
| Predicate | yearTurnedProfessional |
P47763
|
FINISHED |
| Object | 1932 |
—
|
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: 1932 | Statement: [John Byron Nelson Jr., yearTurnedProfessional, 1932]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: yearTurnedProfessional Context triple: [John Byron Nelson Jr., yearTurnedProfessional, 1932]
-
A.
firstYearPlayed
Indicates the year in which an entity (such as a person or team) first began participating in the specified activity or domain.
-
B.
yearTurned
chosen
Indicates the specific year in which an entity changed state, status, or classification (e.g., when it became, reached, or turned into something).
-
C.
beganInYear
Indicates that an event, process, or state started in a specific calendar year.
-
D.
springTrainingStartYear
Indicates the year in which an entity’s spring training period begins.
-
E.
activeYearsInSport
Indicates the span of years during which an entity actively participated in a particular sport.
- 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_69c00825df388190a58742fa9b1aa33d |
completed | March 22, 2026, 3:17 p.m. |
| NER | Named-entity recognition | batch_69c022d4ca788190b20168b20cb1d030 |
completed | March 22, 2026, 5:11 p.m. |
| PD | Predicate disambiguation | batch_69c01b2168508190b64b355cf50034ad |
completed | March 22, 2026, 4:38 p.m. |
Created at: March 22, 2026, 3:42 p.m.