Triple
T21594652
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Criss Cross |
E532866
|
entity |
| Predicate | screenwriter |
P2831
|
FINISHED |
| Object | Daniel Fuchs |
—
|
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 Fuchs | Statement: [Criss Cross, screenwriter, Daniel Fuchs]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Daniel Fuchs Context triple: [Criss Cross, screenwriter, Daniel Fuchs]
-
A.
Daniel Fuchs
chosen
Daniel Fuchs was an American novelist and screenwriter known for his Brooklyn-set fiction and acclaimed Hollywood screenplays, including several classic film noirs.
-
B.
Michael Fuchs
Michael Fuchs is an actor known for his role in the independent drama film "12 and Holding."
-
C.
Michael Fuchs
Michael Fuchs is a businessman and hotelier best known for his ownership stake in New York City's historic Gramercy Park Hotel.
-
D.
Thomas Fuchs
Thomas Fuchs is a German computer scientist and software developer best known for creating the JavaScript libraries script.aculo.us and contributing to Prototype.
-
E.
Peter Fuchs
Peter Fuchs is a notable individual who shares the surname Fuchs, recognized enough to be specifically distinguished among its bearers.
- 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_69e0c46251648190876f0427cf2d321b |
completed | April 16, 2026, 11:13 a.m. |
| NER | Named-entity recognition | batch_69eefae07e388190baf1d67852c7e5db |
completed | April 27, 2026, 5:57 a.m. |
Created at: April 16, 2026, 6:32 p.m.