Triple
T23331042
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Jimmy Chambers |
E591441
|
entity |
| Predicate | member of |
P10
|
FINISHED |
| Object | Londonbeat |
—
|
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: Londonbeat | Statement: [Jimmy Chambers, member of, Londonbeat]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Londonbeat Context triple: [Jimmy Chambers, member of, Londonbeat]
-
A.
Londonbeat
chosen
Londonbeat is a British-American dance-pop band best known for their early 1990s international hit singles and soulful, club-oriented sound.
-
B.
Streets of London
"Streets of London" is a folk song, most famously performed by Ralph McTell, that poignantly highlights urban loneliness and social neglect.
-
C.
London Bar
The London Bar is a professional association of barristers practicing in London, forming part of the wider Bar of England and Wales.
-
D.
London Talking
London Talking was a British television programme, notably hosted by presenter Konnie Huq, that focused on issues and stories related to life in London.
-
E.
London Particular
London Particular is a classic British crime novel by Christianna Brand, featuring her recurring detective Inspector Cockrill in a fog-shrouded murder mystery.
- F. None of above.
- G. Unsure - the case is ambiguous/there is not enough information to decide.
Provenance (2 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_69e25d20156c81908c5c53195bd9c738 |
completed | April 17, 2026, 4:17 p.m. |
| NER | Named-entity recognition | batch_69f197edfbbc81908cb56507cd280737 |
completed | April 29, 2026, 5:32 a.m. |
Created at: April 17, 2026, 5:15 p.m.