Triple
T9480949
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Paul Wiggin |
E228634
|
entity |
| Predicate | professionalPlayingCareerStart |
P67438
|
FINISHED |
| Object | 1957 |
—
|
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: 1957 | Statement: [Paul Wiggin, professionalPlayingCareerStart, 1957]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: professionalPlayingCareerStart Context triple: [Paul Wiggin, professionalPlayingCareerStart, 1957]
-
A.
playedCareerStartYear
chosen
Indicates the calendar year in which an entity’s playing career (such as a professional or competitive role) began.
-
B.
clubCareerStart
Indicates the point in time when an entity begins its professional or organized club-level career.
-
C.
startTimeOfProfessionalCareer
Indicates the point in time when an individual’s professional career formally begins.
-
D.
beganAmateurCareer
Indicates that an entity started its amateur-level career or involvement in a particular field or activity.
-
E.
careerStartAsPlayer
Indicates the point in time or context when an individual began their professional career as a player.
- 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_69ca84730a5081908de282651019bf2f |
completed | March 30, 2026, 2:10 p.m. |
| NER | Named-entity recognition | batch_69cd8018645c8190823d82a93635b345 |
completed | April 1, 2026, 8:29 p.m. |
| PD | Predicate disambiguation | batch_69cca561e6b0819090aa795f3c3a2083 |
completed | April 1, 2026, 4:56 a.m. |
Created at: March 30, 2026, 7:54 p.m.