Triple
T21676035
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Mannish Boy |
E534972
|
entity |
| Predicate | lyricist |
P1360
|
FINISHED |
| Object | Mel London |
—
|
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: Mel London | Statement: [Mannish Boy, lyricist, Mel London]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Mel London Context triple: [Mannish Boy, lyricist, Mel London]
-
A.
Mel London
chosen
Mel London was an American blues songwriter and producer known for penning influential Chicago blues standards in the 1950s and 1960s.
-
B.
George London
George London was a prominent late 17th- and early 18th-century English garden designer and nurseryman known for helping shape formal Baroque landscapes in Britain.
-
C.
John Hurst
John Hurst is a personal name shared by multiple notable individuals across fields such as sports, politics, and the arts.
-
D.
John Lanchbery
John Lanchbery was a renowned British conductor and arranger best known for his influential work in ballet music for companies such as The Royal Ballet.
-
E.
Jack Garland
Jack Garland was a prominent Canadian politician from North Bay, Ontario, who served as a long-time Member of Parliament and community leader.
- 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_69e0c46898008190aa618a4af55bd1ee |
completed | April 16, 2026, 11:13 a.m. |
| NER | Named-entity recognition | batch_69ef8a0f85748190944b9425ffed02ee |
completed | April 27, 2026, 4:08 p.m. |
Created at: April 16, 2026, 6:42 p.m.