Triple
T35805590
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Jazz |
E1035093
|
entity |
| Predicate | trainedAsWrestlerIn |
P184663
|
FINISHED |
| Object | United States |
—
|
NE NERFINISHED |
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: United States | Statement: [Jazz, trainedAsWrestlerIn, United States]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: trainedAsWrestlerIn Context triple: [Jazz, trainedAsWrestlerIn, United States]
-
A.
trainedWrestlersOn
Indicates that one entity has trained wrestlers on or for another entity, such as a team, organization, or event.
-
B.
wrestledWith
Indicates that one entity engaged in a physical wrestling contest or struggle with another entity.
-
C.
managedWrestler
Indicates that one entity served as the manager of another entity in a professional wrestling context.
-
D.
typeOfWrestling
Indicates the specific style or category of wrestling that characterizes a given wrestling activity or event.
-
E.
developedWrestler
Indicates that one entity (such as a trainer, organization, or promotion) played a significant role in training, shaping, or advancing the professional wrestling career of another entity (the wrestler).
- 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_69f76e169bd081909f16cd8c9ee7870c |
completed | May 3, 2026, 3:47 p.m. |
| NER | Named-entity recognition | batch_69f7b365288c8190bcb11fcfba028737 |
completed | May 3, 2026, 8:43 p.m. |
| PD | Predicate disambiguation | batch_69f7b1b8a9fc8190a1279e67a2d12707 |
completed | May 3, 2026, 8:36 p.m. |
| PDg | Predicate description generation | batch_69f7b2f2b9ac8190aa05b8a1aa18ec2d |
completed | May 3, 2026, 8:41 p.m. |
Created at: May 3, 2026, 4:06 p.m.