Triple
T22713177
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Leviathan (1989 film) |
E561654
|
entity |
| Predicate | stars |
P1956
|
FINISHED |
| Object | Daniel Stern |
—
|
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 Stern | Statement: [Leviathan (1989 film), stars, Daniel Stern]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Daniel Stern Context triple: [Leviathan (1989 film), stars, Daniel Stern]
-
A.
Daniel Stern
Daniel Stern is the mayor of the Austrian municipality of Mieders.
-
B.
Daniel Stern
chosen
Daniel Stern is an American actor and director best known for his comedic roles in films like "City Slickers" and the "Home Alone" series, as well as for narrating the television show "The Wonder Years."
-
C.
Leon Eisenberg
Leon Eisenberg was an influential American child psychiatrist and medical educator known for his pioneering work in autism and attention-deficit/hyperactivity disorder (ADHD) research.
-
D.
Shel Kagan
Shel Kagan is a film producer best known for his work on the movie "Loaded."
-
E.
Jonathan Stern
Jonathan Stern is an American film and television producer best known for his work on offbeat comedies such as "Wet Hot American Summer" and various projects for Adult Swim and streaming platforms.
- 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_69e2454f1348819088d83f420925a5c1 |
completed | April 17, 2026, 2:35 p.m. |
| NER | Named-entity recognition | batch_69f1790ab6208190a342f076002324ab |
completed | April 29, 2026, 3:20 a.m. |
Created at: April 17, 2026, 3:18 p.m.