Triple
T18220798
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | The John Larroquette Show |
E436296
|
entity |
| Predicate | usesSettingAs |
P15599
|
FINISHED |
| Object | central narrative location |
—
|
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: central narrative location | Statement: [The John Larroquette Show, usesSettingAs, central narrative location]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: usesSettingAs Context triple: [The John Larroquette Show, usesSettingAs, central narrative location]
-
A.
usedAsSettingFor
chosen
Indicates that one entity serves as the backdrop, location, or environment in which another entity (such as an event, story, or activity) takes place.
-
B.
coversSetting
Indicates that one entity includes or addresses a particular setting or context within its scope.
-
C.
hasSetting
Indicates that an entity takes place, occurs, or exists within a particular environment, context, or location.
-
D.
associatedWithSetting
Indicates that one entity is connected or linked to a particular context, environment, or setting in which it occurs or is relevant.
-
E.
knownAsSettingFor
Indicates that something is recognized or regarded as the typical or notable setting or backdrop for something else.
- 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_69d8b9103a8081908bbb0836fef10efd |
completed | April 10, 2026, 8:47 a.m. |
| NER | Named-entity recognition | batch_69e4e47b5bfc819085c5935c08361ba9 |
completed | April 19, 2026, 2:19 p.m. |
| PD | Predicate disambiguation | batch_69e4332155d88190b106d0dceb4554af |
completed | April 19, 2026, 1:42 a.m. |
Created at: April 10, 2026, 10:32 a.m.