Triple
T21065049
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | The Frank Sinatra Show |
E518945
|
entity |
| Predicate | basedOnOccupationOfHost |
P71047
|
FINISHED |
| Object | 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: singer | Statement: [The Frank Sinatra Show, basedOnOccupationOfHost, singer]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: basedOnOccupationOfHost Context triple: [The Frank Sinatra Show, basedOnOccupationOfHost, 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.
hostOccupation
Indicates that one entity serves as the primary job, profession, or role held by another entity.
-
C.
basedOnProfession
chosen
Indicates that the relationship or action is determined or derived from a person’s profession or occupational role.
-
D.
endedOccupationOf
Indicates that one entity brought another entity’s occupation or control of a place or position to an end.
-
E.
occupantIndustry
Indicates the industry or sector in which an occupant (such as a tenant or user of a space) operates.
- 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_69e0b505ef108190b25dd4033e2ff7eb |
completed | April 16, 2026, 10:08 a.m. |
| NER | Named-entity recognition | batch_69e6feb3799c8190bebabb087b917321 |
completed | April 21, 2026, 4:36 a.m. |
| PD | Predicate disambiguation | batch_69e5dbf9d71881908cd85dfc37db93ca |
completed | April 20, 2026, 7:55 a.m. |
Created at: April 16, 2026, 2:44 p.m.