Triple
T20253574
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Bruno Ganz |
E498622
|
entity |
| Predicate | child |
P120
|
FINISHED |
| Object | Daniel Ganz |
—
|
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: Daniel Ganz | Statement: [Bruno Ganz, child, Daniel Ganz]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Daniel Ganz Context triple: [Bruno Ganz, child, Daniel Ganz]
-
A.
Daniel Ganz
chosen
Daniel Ganz is the son of acclaimed Swiss actor Bruno Ganz.
-
B.
Andrew Meyer
Andrew Meyer is a fictional character in the television series "Veep," known as the ex-husband of main character Selina Meyer and the father of her daughter Catherine.
-
C.
Michael Engler
Michael Engler is an American television and film director and producer known for his work on acclaimed series such as "Downton Abbey," "Sex and the City," and "30 Rock."
-
D.
Michael Gottlieb
Michael Gottlieb was an American film director and screenwriter best known for directing the 1987 fantasy comedy "Mannequin" and other lighthearted Hollywood comedies.
-
E.
Daniel Zelman
Daniel Zelman is an American actor, screenwriter, and television producer known for co-creating the legal thriller series "Damages."
- 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_69da6274c58c81909c646eabed6f4f30 |
completed | April 11, 2026, 3:02 p.m. |
| NER | Named-entity recognition | batch_69e673aa42348190852ae8313f4494ca |
completed | April 20, 2026, 6:42 p.m. |
Created at: April 11, 2026, 11:41 p.m.