Triple
T3341182
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | U.S. broadcast television networks |
E70263
|
entity |
| Predicate | typicalCoverage |
P41336
|
FINISHED |
| Object | nationwide |
—
|
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: nationwide | Statement: [U.S. broadcast television networks, typicalCoverage, nationwide]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: typicalCoverage Context triple: [U.S. broadcast television networks, typicalCoverage, nationwide]
-
A.
typicallyCovers
chosen
Indicates that one entity is the kind of thing that usually or normally includes, addresses, or encompasses another entity.
-
B.
typeOfCoverage
Indicates the specific kind or category of coverage that applies in a given context (such as insurance, service, or protection).
-
C.
providesCoverage
Indicates that one entity supplies protection, insurance, or service coverage to another entity or for a specified risk or scope.
-
D.
regionCoverage
Indicates that one entity geographically spans, includes, or serves the area defined by another entity.
-
E.
isFrequentlyCovered
Indicates that an entity is regularly or commonly reported on, discussed, or featured, especially in media or informational sources.
- 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_69ad85a405e48190b6e68de7cf9f319e |
completed | March 8, 2026, 2:20 p.m. |
| NER | Named-entity recognition | batch_69adb1c0ae44819091c851569eaf4565 |
completed | March 8, 2026, 5:28 p.m. |
| PD | Predicate disambiguation | batch_69ada42df1d48190874bb05f95deefde |
completed | March 8, 2026, 4:30 p.m. |
Created at: March 8, 2026, 3:12 p.m.