Triple
T10467156
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | The Recruit |
E246826
|
entity |
| Predicate | musicBy |
P1952
|
FINISHED |
| Object | Klaus Badelt |
E183808
|
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: Klaus Badelt | Statement: [The Recruit, musicBy, Klaus Badelt]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Klaus Badelt Context triple: [The Recruit, musicBy, Klaus Badelt]
-
A.
Klaus Badelt
chosen
Klaus Badelt is a German film composer best known for his work on major Hollywood scores such as "Pirates of the Caribbean: The Curse of the Black Pearl."
-
B.
Klaus Kiessler
Klaus Kiessler is a German architect known for designing the main building of the Topography of Terror documentation center in Berlin.
-
C.
Klaus Thiel
Klaus Thiel is a German athlete known for competing in racewalking at international track and field events.
-
D.
Klaus Wolter
Klaus Wolter is a climate scientist known for creating the Multivariate ENSO Index, a key tool for monitoring and analyzing El Niño–Southern Oscillation variability.
-
E.
Jürgen Büscher
Jürgen Büscher is a screenwriter best known for co-writing the 1993 German war film "Stalingrad."
- 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_69d381c16c248190a2fe5b471e584e9c |
completed | April 6, 2026, 9:49 a.m. |
| NER | Named-entity recognition | batch_69d5092e3230819098ab444f73c9bd40 |
completed | April 7, 2026, 1:39 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69f671788ec88190852df74698bc4518 |
completed | May 2, 2026, 9:49 p.m. |
Created at: April 6, 2026, 12:20 p.m.