Triple
T19872750
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Keyshia Cole: The Way It Is |
E477559
|
entity |
| Predicate | basedOnOccupationOfSubject |
P71047
|
FINISHED |
| Object | R&B singer |
—
|
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: R&B singer | Statement: [Keyshia Cole: The Way It Is, basedOnOccupationOfSubject, R&B singer]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: basedOnOccupationOfSubject Context triple: [Keyshia Cole: The Way It Is, basedOnOccupationOfSubject, R&B singer]
-
A.
basedOnCareerOf
Indicates that something (such as a work, character, or storyline) is derived from, inspired by, or modeled on the career or professional life of a particular person.
-
B.
basedOnProfession
chosen
Indicates that the relationship or action is determined or derived from a person’s profession or occupational role.
-
C.
basedOnSubject
Indicates that something is derived from, influenced by, or determined according to a particular subject.
-
D.
subjectOccupation
Indicates that the subject holds or performs a particular job, profession, or role as their occupation.
-
E.
basedOnSubjectOf
Indicates that something is derived from, informed by, or constructed using the subject matter or content of another entity.
- 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_69d8e51e7d948190aedbcd6c30361c39 |
completed | April 10, 2026, 11:55 a.m. |
| NER | Named-entity recognition | batch_69e658d826f88190be04188997952d1b |
completed | April 20, 2026, 4:48 p.m. |
| PD | Predicate disambiguation | batch_69e537e8c4e481909fe95d795b4864e7 |
completed | April 19, 2026, 8:15 p.m. |
Created at: April 10, 2026, 1:51 p.m.