Triple
T21511253
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Hush...Hush, Sweet Charlotte |
E530724
|
entity |
| Predicate | musicBy |
P1952
|
FINISHED |
| Object | Frank De Vol |
—
|
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: Frank De Vol | Statement: [Hush...Hush, Sweet Charlotte, musicBy, Frank De Vol]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Frank De Vol Context triple: [Hush...Hush, Sweet Charlotte, musicBy, Frank De Vol]
-
A.
Frank De Vol
chosen
Frank De Vol was an American arranger, composer, and conductor best known for his film and television scores and theme music during the mid-20th century.
-
B.
Frank de Grave
Frank de Grave is a Dutch politician who served as Minister of Defence and has been active in various governmental and public sector roles in the Netherlands.
-
C.
Peter deVroede
Peter deVroede is a technology entrepreneur best known as a founder of the podcast platform Stitcher.
-
D.
Peter De Vries
Peter De Vries was an American novelist and humorist known for his witty, satirical fiction and contributions to The New Yorker.
-
E.
Don Otten
Don Otten was an American professional basketball center who played in the early years of the NBA, including for the Tri-Cities Blackhawks.
- 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_69e0c45c81f08190a6b8bbb70a45aae7 |
completed | April 16, 2026, 11:13 a.m. |
| NER | Named-entity recognition | batch_69e9ea863b18819080e3ff249b10ec28 |
completed | April 23, 2026, 9:46 a.m. |
Created at: April 16, 2026, 6:25 p.m.