Triple
T24675141
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | BBC radio studios |
E610962
|
entity |
| Predicate | networkCoverageArea |
P4903
|
FINISHED |
| Object | international (via BBC World Service) |
—
|
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: international (via BBC World Service) | Statement: [BBC radio studios, networkCoverageArea, international (via BBC World Service)]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: networkCoverageArea Context triple: [BBC radio studios, networkCoverageArea, international (via BBC World Service)]
-
A.
networkCoverage
chosen
Indicates the extent to which a network’s signal or service is available across a given area or to specific entities.
-
B.
hasAreaOfCoverage
Indicates that an entity provides services, influence, or applicability within a specified geographic or conceptual region.
-
C.
networkArea
Indicates that one entity defines, covers, or is responsible for a specific network area associated with another entity.
-
D.
dataCoverage
Indicates the extent or proportion of relevant data that is included, captured, or represented within a given dataset or system.
-
E.
mapCoverage
Indicates the extent or area that is represented, covered, or included by a particular map.
- 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_69e2c4d5c2dc8190ac857dea25ec6ce9 |
completed | April 17, 2026, 11:40 p.m. |
| NER | Named-entity recognition | batch_69f422aee0408190899efe7e24ef2b40 |
completed | May 1, 2026, 3:49 a.m. |
| PD | Predicate disambiguation | batch_69f420e92cc88190a803aecdae78a051 |
completed | May 1, 2026, 3:41 a.m. |
Created at: April 18, 2026, 3:02 a.m.