Triple
T14028420
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Scary Movie 4 |
E337523
|
entity |
| Predicate | producer |
P490
|
FINISHED |
| Object | Robert K. Weiss |
E332323
|
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: Robert K. Weiss | Statement: [Scary Movie 4, producer, Robert K. Weiss]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Robert K. Weiss Context triple: [Scary Movie 4, producer, Robert K. Weiss]
-
A.
Robert K. Weiss
chosen
Robert K. Weiss is an American film and television producer best known for his work on comedy projects such as "The Naked Gun" series and collaborations with the Zucker brothers.
-
B.
Daniel H. Weiss
Daniel H. Weiss is an American art historian and academic leader who served as president and CEO of New York’s Metropolitan Museum of Art.
-
C.
David C. Weiss
David C. Weiss is an American attorney who serves as a U.S. Special Counsel and has been a key federal prosecutor in high-profile political and financial investigations.
-
D.
John Weiss
John Weiss is a relatively obscure individual whose specific notability is not clearly established from the given information.
-
E.
Peter J. Weinberger
Peter J. Weinberger is an American computer scientist known for his contributions to programming languages and tools at Bell Labs, including co-creating the AWK programming language.
- 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_69d81c6543a48190bd5ba93d7419e797 |
completed | April 9, 2026, 9:38 p.m. |
| NER | Named-entity recognition | batch_69de2fa830ac81908cb7df7c9e81e42a |
completed | April 14, 2026, 12:14 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69fd27fdad4c8190bf5ce5d676284e62 |
completed | May 8, 2026, 12:02 a.m. |
Created at: April 9, 2026, 10:20 p.m.