Triple
T22366700
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Elser – Er hätte die Welt verändert |
E552922
|
entity |
| Predicate | editedBy |
P1954
|
FINISHED |
| Object | Alexander Dittner |
—
|
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: Alexander Dittner | Statement: [Elser – Er hätte die Welt verändert, editedBy, Alexander Dittner]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Alexander Dittner Context triple: [Elser – Er hätte die Welt verändert, editedBy, Alexander Dittner]
-
A.
Alexander Dittner
chosen
Alexander Dittner is a film editor best known for his work on the 2013 animated film "Tarzan."
-
B.
Daniel P. Livermore
Daniel P. Livermore was the husband of prominent American abolitionist and women's rights advocate Mary Livermore.
-
C.
Eric L. Zinterhofer
Eric L. Zinterhofer is an American private equity investor and media executive known for his leadership roles in the telecommunications and cable industry.
-
D.
Michael Wimer
Michael Wimer is a film and television producer best known for his work on genre projects such as the science fiction series "Outsiders."
-
E.
Daniel W. Herzog
Daniel W. Herzog is an American Anglican bishop best known for serving as the Bishop of the Episcopal Diocese of Albany in New York.
- 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_69e11e4affcc8190ba7c27d29062558d |
completed | April 16, 2026, 5:37 p.m. |
| NER | Named-entity recognition | batch_69f1580074dc819091305ac7017000d3 |
completed | April 29, 2026, 12:59 a.m. |
Created at: April 16, 2026, 8:44 p.m.