Triple
T10917874
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Hidden Agenda |
E257870
|
entity |
| Predicate | producer |
P490
|
FINISHED |
| Object | Eric Fellner |
E136678
|
NE FINISHED |
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: Eric Fellner | Statement: [Hidden Agenda, producer, Eric Fellner]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Eric Fellner Context triple: [Hidden Agenda, producer, Eric Fellner]
-
A.
Eric Fellner
chosen
Eric Fellner is a British film producer and co-chairman of Working Title Films, known for overseeing numerous successful UK and international movies.
-
B.
Eric Pohlmann
Eric Pohlmann was an Austrian-born character actor best known for providing the original voice of the villain Ernst Stavro Blofeld in the early James Bond films.
-
C.
Eric Schoffstall
Eric Schoffstall is a software developer best known for creating Gulp, a popular JavaScript-based task runner used in web development build workflows.
-
D.
Bill Steinkellner
Bill Steinkellner is an American television writer and producer best known for his work on popular sitcoms, often in collaboration with his wife Cheri Steinkellner.
-
E.
Don Ettlinger
Don Ettlinger was a screenwriter active in early 20th-century American cinema, known for adapting popular literary works for the screen.
- F. None of above.
- G. Unsure - the case is ambiguous/there is not enough information to decide.
Provenance (3 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_69d6aa864ed88190818280ab6791d065 |
completed | April 8, 2026, 7:20 p.m. |
| NER | Named-entity recognition | batch_69d7707ebdcc8190b42cafe21c667c82 |
completed | April 9, 2026, 9:25 a.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69ee85e044e881909d426f7121dd89e1 |
completed | April 26, 2026, 9:38 p.m. |
Created at: April 8, 2026, 9:22 p.m.