Triple
T23128094
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Erwin Bootz |
E577091
|
entity |
| Predicate | name |
P16
|
FINISHED |
| Object | Erwin Bootz |
—
|
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: Erwin Bootz | Statement: [Erwin Bootz, name, Erwin Bootz]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Erwin Bootz Context triple: [Erwin Bootz, name, Erwin Bootz]
-
A.
Erwin Bootz
chosen
Erwin Bootz was a German pianist best known as a member of the renowned vocal ensemble the Comedian Harmonists.
-
B.
Paul Kopf
Paul Kopf is a musician best known as a member of the 1960s American psychedelic rock band The Seeds.
-
C.
Rudi Fehr
Rudi Fehr was a German-born American film editor known for his work on numerous Hollywood films from the 1940s through the 1970s.
-
D.
Eddy Hartenstein
Eddy Hartenstein is an American media executive best known for leading the development and growth of the satellite television service DirecTV.
-
E.
Karl Weschke
Karl Weschke was a German-born British painter known for his expressive, often somber figurative and landscape works and his association with the post-war St Ives art scene in Cornwall.
- 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_69e245f7b0e481909c473ff4e6a54e2c |
completed | April 17, 2026, 2:38 p.m. |
| NER | Named-entity recognition | batch_69f18e857b40819081f9df03fff64d48 |
completed | April 29, 2026, 4:52 a.m. |
Created at: April 17, 2026, 3:59 p.m.