Triple
T23293723
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Vincent Van Patten |
E590104
|
entity |
| Predicate | turnedProInTennis |
P9282
|
FINISHED |
| Object | 1976 |
—
|
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: 1976 | Statement: [Vincent Van Patten, turnedProInTennis, 1976]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: turnedProInTennis Context triple: [Vincent Van Patten, turnedProInTennis, 1976]
-
A.
turnedPro
chosen
Indicates that an individual transitioned from amateur status to professional status in a particular field or activity.
-
B.
tennisStatus
Indicates the current state or condition of an entity in the context of tennis, such as whether they are playing, available, or in a particular match-related status.
-
C.
positionInTennis
Indicates the specific role or court location a player occupies during a tennis match or point.
-
D.
servedOnCourt
Indicates that a person held an official judicial position on a particular court.
-
E.
turnType
Indicates the specific kind or category of turn being made in a movement or path (e.g., left turn, right turn, U-turn).
- 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_69e25d1af9d88190a0b9b5e8fa608618 |
completed | April 17, 2026, 4:17 p.m. |
| NER | Named-entity recognition | batch_69f196ccd9b481909ab5d3504640025e |
completed | April 29, 2026, 5:27 a.m. |
| PD | Predicate disambiguation | batch_69effcf325f88190b320268c3c551abb |
completed | April 28, 2026, 12:18 a.m. |
Created at: April 17, 2026, 5:02 p.m.