Triple
T16213264
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Monday Morning Podcast |
E393518
|
entity |
| Predicate | primaryHostOccupation |
P39157
|
FINISHED |
| Object | stand-up comedian |
—
|
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: stand-up comedian | Statement: [Monday Morning Podcast, primaryHostOccupation, stand-up comedian]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: primaryHostOccupation Context triple: [Monday Morning Podcast, primaryHostOccupation, stand-up comedian]
-
A.
hostOccupation
chosen
Indicates that one entity serves as the primary job, profession, or role held by another entity.
-
B.
hasPrimaryOccupants
Indicates that certain entities are the main or principal occupants of another entity (such as a space, structure, or location).
-
C.
primaryHosts
Indicates that the subject serves as the main or principal host for the object, such as an organism, event, or service.
-
D.
numberOfHospitalized
Indicates the count of individuals who have been admitted to a hospital for medical care.
-
E.
secondHolderOccupation
Indicates the occupation or job role held by the second participant in the relationship.
- 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_69d87f1f5bd08190bd01cac0d5b9d2ef |
completed | April 10, 2026, 4:39 a.m. |
| NER | Named-entity recognition | batch_69e227f2c1288190bfaed49c364bfa22 |
completed | April 17, 2026, 12:30 p.m. |
| PD | Predicate disambiguation | batch_69e219e94a448190b73a4e6aa374eb4a |
completed | April 17, 2026, 11:30 a.m. |
Created at: April 10, 2026, 5:03 a.m.