Triple
T11138847
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Debbie Wiseman |
E263485
|
entity |
| Predicate | employer |
P7
|
FINISHED |
| Object |
Classic FM
Classic FM is a UK-based national commercial radio station dedicated to accessible classical music programming and popular orchestral works.
|
E907459
|
NE FINISHED |
How this triple was built (4 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: Classic FM | Statement: [Debbie Wiseman, employer, Classic FM]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Classic FM Context triple: [Debbie Wiseman, employer, Classic FM]
-
A.
Classic
Classic is the entry-level membership tier in the Miles&Smiles frequent flyer loyalty program.
-
B.
BBC Radio 3
BBC Radio 3 is a British national radio station operated by the BBC, best known for its focus on classical music, opera, jazz, and arts programming.
-
C.
BBC Radio 1
BBC Radio 1 is a major UK national radio station focused on contemporary popular music and youth-oriented programming.
-
D.
BBC Radio 2
BBC Radio 2 is a major UK national radio station known for its broad mix of popular music, entertainment, and speech programming aimed primarily at adult listeners.
-
E.
Capital Radio
Capital Radio is a major London-based commercial radio station that became widely known in the 1970s and 1980s for its popular music programming and influential presenters.
- F. None of above. chosen
- G. Unsure - the case is ambiguous/there is not enough information to decide.
NEDg
Description generation
gpt-5.1
Instruction
Generate a one-sentence description of the target entity. You are given a context triple in the form (subject, predicate, object), where the object is the target entity. # Instructions Use the triple to infer relevant information about the entity. Describe the entity based on what is most defining, well-known. Avoid repeating the information from the triple, unless really essential. # Response Format Return only the sentence: "Description: [one-sentence description of the target entity]"
Input
Entity: Classic FM Triple: [Debbie Wiseman, employer, Classic FM]
Generated description
Classic FM is a UK-based national commercial radio station dedicated to accessible classical music programming and popular orchestral works.
NED2
Entity disambiguation (via description)
gpt-5-mini-2025-08-07
Target entity: Classic FM Target entity description: Classic FM is a UK-based national commercial radio station dedicated to accessible classical music programming and popular orchestral works.
-
A.
Classic
Classic is the entry-level membership tier in the Miles&Smiles frequent flyer loyalty program.
-
B.
BBC Radio 3
BBC Radio 3 is a British national radio station operated by the BBC, best known for its focus on classical music, opera, jazz, and arts programming.
-
C.
BBC Radio 1
BBC Radio 1 is a major UK national radio station focused on contemporary popular music and youth-oriented programming.
-
D.
BBC Radio 2
BBC Radio 2 is a major UK national radio station known for its broad mix of popular music, entertainment, and speech programming aimed primarily at adult listeners.
-
E.
Capital Radio
Capital Radio is a major London-based commercial radio station that became widely known in the 1970s and 1980s for its popular music programming and influential presenters.
- F. None of above. chosen
Provenance (5 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_69d6aa9c0ba08190bbd19c217489b755 |
completed | April 8, 2026, 7:21 p.m. |
| NER | Named-entity recognition | batch_69d7e85f2ea48190bf1ff63af1d7d236 |
completed | April 9, 2026, 5:56 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69e442030b588190bc958030f30b648a |
completed | April 19, 2026, 2:46 a.m. |
| NEDg | Description generation | batch_69e44c09dd5c8190bddf3dd109a639ba |
completed | April 19, 2026, 3:29 a.m. |
| NED2 | Entity disambiguation (via description) | batch_69e451274ce48190a05f1d37f972c36c |
completed | April 19, 2026, 3:51 a.m. |
Created at: April 8, 2026, 9:28 p.m.