Triple
T33802601
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Lynn Barber |
E866267
|
entity |
| Predicate | notableInterviewSubjects |
P54543
|
FINISHED |
| Object | artists |
—
|
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: artists | Statement: [Lynn Barber, notableInterviewSubjects, artists]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: notableInterviewSubjects Context triple: [Lynn Barber, notableInterviewSubjects, artists]
-
A.
notableInterviewee
chosen
Indicates that a person has been interviewed by another person or organization in a way considered significant or noteworthy.
-
B.
notableIndividuals
Indicates that certain individuals are recognized as particularly important, famous, or influential in relation to something.
-
C.
holderNotableFor
Indicates that a holder (such as a person or organization) is particularly known or recognized for a specific role, achievement, work, or characteristic.
-
D.
notablePersonnel
Indicates that the subject has associated individuals who are particularly important, distinguished, or prominent in relation to it.
-
E.
notableFigureFeatured
Indicates that a notable or prominent individual is highlighted, showcased, or given special attention in the associated context or medium.
- 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_69f3499057fc81909d862b1309a3bd71 |
completed | April 30, 2026, 12:22 p.m. |
| NER | Named-entity recognition | batch_6a037e0953908190b2930b3c06a40129 |
completed | May 12, 2026, 7:22 p.m. |
| PD | Predicate disambiguation | batch_6a0379f6c3308190b954f7810214ceed |
completed | May 12, 2026, 7:05 p.m. |
Created at: May 1, 2026, 1:46 a.m.