Triple
T23284635
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Around the World |
E588953
|
entity |
| Predicate | composer |
P1361
|
FINISHED |
| Object | Thomas Bangalter |
—
|
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: Thomas Bangalter | Statement: [Around the World, composer, Thomas Bangalter]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Thomas Bangalter Context triple: [Around the World, composer, Thomas Bangalter]
-
A.
Thomas Bangalter
chosen
Thomas Bangalter is a French electronic musician, DJ, and record producer best known as one half of the influential duo Daft Punk.
-
B.
Laurent Garnier
Laurent Garnier is a pioneering French DJ, producer, and electronic music figure known for shaping the global techno and house scenes since the late 1980s.
-
C.
Jean-Benoît Dunckel
Jean-Benoît Dunckel is a French musician and composer best known as one half of the electronic music duo Air.
-
D.
Juan Atkins
Juan Atkins is an American electronic musician and producer widely regarded as one of the originators of techno music and a central figure in the Detroit techno movement.
-
E.
Paul van Dyk
Paul van Dyk is a German DJ and producer widely regarded as one of the pioneers and leading figures of the trance music genre.
- 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_69e25d16e2c08190a291de254703129e |
completed | April 17, 2026, 4:17 p.m. |
| NER | Named-entity recognition | batch_69f196454b4c8190a797537ce8912241 |
completed | April 29, 2026, 5:25 a.m. |
Created at: April 17, 2026, 4:59 p.m.