Triple
T19474203
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | White Fang (1991 film) |
E487201
|
entity |
| Predicate | screenwriter |
P2831
|
FINISHED |
| Object | Nick Thiel |
—
|
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: Nick Thiel | Statement: [White Fang (1991 film), screenwriter, Nick Thiel]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Nick Thiel Context triple: [White Fang (1991 film), screenwriter, Nick Thiel]
-
A.
Nick Thiel
chosen
Nick Thiel is a television producer and writer best known for his work as an executive producer on the crime-comedy series "White Collar."
-
B.
Michael Thiel
Michael Thiel is an individual notable enough to be specifically distinguished from others sharing the surname Thiel.
-
C.
Andrew Thielk
Andrew Thielk is a writer known for his work on the song "Hey Porsche."
-
D.
Chris Sievernich
Chris Sievernich is a German film producer best known for his work on acclaimed art-house and independent films, including Wim Wenders’ "Paris, Texas."
-
E.
Chris Weinke
Chris Weinke is a former American football quarterback best known for leading Florida State University to a national championship and winning the Heisman Trophy before playing in the NFL.
- 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_69d8e8d924388190b847cb15bb3d0aff |
completed | April 10, 2026, 12:11 p.m. |
| NER | Named-entity recognition | batch_69e633ef69508190b0d71ef663ba8977 |
completed | April 20, 2026, 2:10 p.m. |
Created at: April 10, 2026, 1:39 p.m.