Triple
T23540873
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Daniel Licht |
E577742
|
entity |
| Predicate | name |
P16
|
FINISHED |
| Object | Daniel Licht |
—
|
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 Licht | Statement: [Daniel Licht, name, Daniel Licht]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Daniel Licht Context triple: [Daniel Licht, name, Daniel Licht]
-
A.
Daniel Licht
chosen
Daniel Licht was an American composer best known for his dark, atmospheric scores for film and television, particularly the acclaimed crime drama series "Dexter."
-
B.
Michael Seitzman
Michael Seitzman is an American screenwriter and producer known for his work on films such as "North Country" and for creating and producing several television series.
-
C.
Jeremy Leven
Jeremy Leven is an American screenwriter, director, and novelist known for adapting romantic and character-driven stories for film, including the hit movie "The Notebook."
-
D.
Jeffrey Blitz
Jeffrey Blitz is an American film and television director and producer known for his work on projects like the documentary "Spellbound," the comedy "Rocket Science," and episodes of "The Office."
-
E.
Brian Silverstein
Brian Silverstein is an individual notable enough to be recognized as a prominent bearer of the surname Silverstein.
- 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_69e245f9d5d08190a4a20004e1784e20 |
completed | April 17, 2026, 2:38 p.m. |
| NER | Named-entity recognition | batch_69f1ae1b3a8c8190b5b6a58f0476c5d2 |
completed | April 29, 2026, 7:07 a.m. |
Created at: April 17, 2026, 6:10 p.m.