Triple
T3203984
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | KMOX (early career) |
E67116
|
entity |
| Predicate | stationFormat |
P46140
|
FINISHED |
| Object | news/talk and sports |
—
|
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: news/talk and sports | Statement: [KMOX (early career), stationFormat, news/talk and sports]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: stationFormat Context triple: [KMOX (early career), stationFormat, news/talk and sports]
-
A.
stationType
Indicates the specific category or classification of a station based on its function, services, or operational characteristics.
-
B.
stationName
Indicates the name assigned to a particular station in the relationship.
-
C.
stationNumber
Indicates the specific station identifier or code assigned to an entity within a system or network.
-
D.
stationLayout
Indicates the spatial arrangement and structural organization of elements within a station.
-
E.
stationComplex
Indicates a relationship where one entity is a station complex that encompasses or is associated with another station-related entity.
- F. None of above. chosen
Provenance (4 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_69ad8589bd988190afa7ed2bdffb7b33 |
completed | March 8, 2026, 2:19 p.m. |
| NER | Named-entity recognition | batch_69adaa54124c8190a22089ce2eaedab5 |
completed | March 8, 2026, 4:56 p.m. |
| PD | Predicate disambiguation | batch_69ad9e078f7c8190813d9fcb4f5071fb |
completed | March 8, 2026, 4:04 p.m. |
| PDg | Predicate description generation | batch_69ada0f9259c8190afbc5ad0fa55436b |
completed | March 8, 2026, 4:16 p.m. |
Created at: March 8, 2026, 3:07 p.m.