Triple
T15099344
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Sweet Charity |
E360620
|
entity |
| Predicate | orchestrator |
P4735
|
FINISHED |
| Object | Ralph Burns |
E527596
|
NE 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: Ralph Burns | Statement: [Sweet Charity, orchestrator, Ralph Burns]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Ralph Burns Context triple: [Sweet Charity, orchestrator, Ralph Burns]
-
A.
Ralph Burns
chosen
Ralph Burns was an American jazz pianist, composer, and arranger renowned for his influential big band work and acclaimed film scores.
-
B.
Ralph Newbery
Ralph Newbery was the father of Argentine aviation pioneer Jorge Newbery and a member of the Newbery family associated with early aviation history in Argentina.
-
C.
Ralph Hart
Ralph Hart is an actor best known for his role on the classic American television sitcom "The Lucy Show."
-
D.
Ralph Fell
Ralph Fell was an English Jesuit priest and scholar active in the late 17th and early 18th centuries.
-
E.
Ralph Partridge
Ralph Partridge was an English editor and member of the Bloomsbury Group, closely associated with figures like Lytton Strachey and Dora Carrington.
- F. None of above.
- G. Unsure - the case is ambiguous/there is not enough information to decide.
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_69d85a035aa88190b52a139d3a1b7b6d |
completed | April 10, 2026, 2:01 a.m. |
| NER | Named-entity recognition | batch_69e0054f00388190a5123d9f4a869b96 |
completed | April 15, 2026, 9:38 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69fedd24523081908cf12a5d6bdd634d |
completed | May 9, 2026, 7:07 a.m. |
Created at: April 10, 2026, 3:04 a.m.