Triple
T23217314
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Peter Schlessel |
E580783
|
entity |
| Predicate | knownAs |
P39
|
FINISHED |
| Object | Peter Schlessel |
—
|
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: Peter Schlessel | Statement: [Peter Schlessel, knownAs, Peter Schlessel]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Peter Schlessel Context triple: [Peter Schlessel, knownAs, Peter Schlessel]
-
A.
Peter Schlessel
chosen
Peter Schlessel is an American film executive and producer best known for leading and founding major independent film companies, including FilmDistrict.
-
B.
Peter Schilling
Peter Schilling is a German synth-pop musician best known internationally for his 1983 hit single "Major Tom (Coming Home)."
-
C.
Guy Schuessler
Guy Schuessler is a British actor and theatre professional best known as the husband of acclaimed stage and screen actress Dame Harriet Walter.
-
D.
Peter Schweger
Peter Schweger is a German architect known for designing prominent contemporary buildings, including major high-rise projects.
-
E.
Peter Schink
Peter Schink is a film editor known for his work on the 1996 action film "Barb Wire."
- 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_69e2460389408190be74f41d217799a9 |
completed | April 17, 2026, 2:38 p.m. |
| NER | Named-entity recognition | batch_69f19165949c81908e4d66a8a2b0a25a |
completed | April 29, 2026, 5:04 a.m. |
Created at: April 17, 2026, 4:08 p.m.