Triple
T35269152
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | The Happy Homemaker |
E1018615
|
entity |
| Predicate | fictionalBroadcastStation |
P147832
|
FINISHED |
| Object | WJM-TV Minneapolis |
—
|
NE NERFINISHED |
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: WJM-TV Minneapolis | Statement: [The Happy Homemaker, fictionalBroadcastStation, WJM-TV Minneapolis]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: fictionalBroadcastStation Context triple: [The Happy Homemaker, fictionalBroadcastStation, WJM-TV Minneapolis]
-
A.
fictionalBroadcastType
Indicates that the relationship specifies the type or category of a fictional broadcast associated with an entity.
-
B.
hasFictionalRadioStation
Indicates that an entity includes, features, or is associated with a fictional radio station within its context or content.
-
C.
broadcastStation
chosen
Indicates that one entity functions as a broadcast station that transmits content or signals to an audience or network.
-
D.
hasFictionalTubeStation
Indicates that an entity features or is associated with a tube (subway) station that exists only in fiction rather than in reality.
-
E.
fictionalChannelCategory
Indicates that a communication channel belongs to a category that exists only in a fictional or imagined context.
- 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_69f76de5c4788190896ad598ae7d6bc6 |
completed | May 3, 2026, 3:46 p.m. |
| NER | Named-entity recognition | batch_69feff70fbec8190b1ff5f943f29613e |
completed | May 9, 2026, 9:33 a.m. |
| PD | Predicate disambiguation | batch_69fefbcd5b7881909cfe52b32f8a4301 |
completed | May 9, 2026, 9:18 a.m. |
Created at: May 3, 2026, 4:02 p.m.