Triple
T23558635
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Re-Dunn |
E579158
|
entity |
| Predicate | showcasesCareerAspect |
P7222
|
FINISHED |
| Object | Ronnie Dunn's work outside Brooks & Dunn |
—
|
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: Ronnie Dunn's work outside Brooks & Dunn | Statement: [Re-Dunn, showcasesCareerAspect, Ronnie Dunn's work outside Brooks & Dunn]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: showcasesCareerAspect Context triple: [Re-Dunn, showcasesCareerAspect, Ronnie Dunn's work outside Brooks & Dunn]
-
A.
managedCareerOf
Indicates that one entity was responsible for overseeing, directing, or handling the professional career of another entity.
-
B.
describesCareerOf
chosen
Indicates that one entity provides a description or characterization of the professional career of another entity.
-
C.
collegeCareerHighlight
Indicates a notable achievement, performance, or milestone that stands out as especially significant within an individual's college career.
-
D.
settingOfCareer
Indicates the primary environment, context, or domain in which a person’s career takes place or is situated.
-
E.
careerAssists
Indicates the total number of assists a player has recorded over the entire span of their professional or competitive career.
- 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_69e245fe24588190888f3aec8407d8e3 |
completed | April 17, 2026, 2:38 p.m. |
| NER | Named-entity recognition | batch_69f1af6663e0819081d654da38cf3aa9 |
completed | April 29, 2026, 7:12 a.m. |
| PD | Predicate disambiguation | batch_69f118afabd88190bd88f49597d120e8 |
completed | April 28, 2026, 8:29 p.m. |
Created at: April 17, 2026, 6:12 p.m.