Triple
T21536933
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Misconduct |
E531371
|
entity |
| Predicate | producer |
P490
|
FINISHED |
| Object |
Stan Wertlieb
Stan Wertlieb is a film producer known for his work on action and genre movies, including the thriller "Misconduct."
|
E1494485
|
NE FINISHED |
How this triple was built (4 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: Stan Wertlieb | Statement: [Misconduct, producer, Stan Wertlieb]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Stan Wertlieb Context triple: [Misconduct, producer, Stan Wertlieb]
-
A.
Martin Weinberg
Martin Weinberg is a sociologist known for his influential research on human sexuality, sexual deviance, and the social construction of sexual norms.
-
B.
Ben D. Waisbren
Ben D. Waisbren is a film producer known for financing and producing major studio and independent movies.
-
C.
Steven Baigelman
Steven Baigelman is an American screenwriter and producer known for his work on biographical and crime dramas in film and television.
-
D.
Adam B. Stern
Adam B. Stern is a film producer known for his work on the movie "Café Society."
-
E.
Justin Furstenfeld
Justin Furstenfeld is an American singer, songwriter, and guitarist best known as the lead vocalist and primary lyricist of the rock band Blue October.
- F. None of above. chosen
- G. Unsure - the case is ambiguous/there is not enough information to decide.
NEDg
Description generation
gpt-5.1
Instruction
Generate a one-sentence description of the target entity. You are given a context triple in the form (subject, predicate, object), where the object is the target entity. # Instructions Use the triple to infer relevant information about the entity. Describe the entity based on what is most defining, well-known. Avoid repeating the information from the triple, unless really essential. # Response Format Return only the sentence: "Description: [one-sentence description of the target entity]"
Input
Entity: Stan Wertlieb Triple: [Misconduct, producer, Stan Wertlieb]
Generated description
Stan Wertlieb is a film producer known for his work on action and genre movies, including the thriller "Misconduct."
NED2
Entity disambiguation (via description)
gpt-5-mini-2025-08-07
Target entity: Stan Wertlieb Target entity description: Stan Wertlieb is a film producer known for his work on action and genre movies, including the thriller "Misconduct."
-
A.
Martin Weinberg
Martin Weinberg is a sociologist known for his influential research on human sexuality, sexual deviance, and the social construction of sexual norms.
-
B.
Ben D. Waisbren
Ben D. Waisbren is a film producer known for financing and producing major studio and independent movies.
-
C.
Steven Baigelman
Steven Baigelman is an American screenwriter and producer known for his work on biographical and crime dramas in film and television.
-
D.
Adam B. Stern
Adam B. Stern is a film producer known for his work on the movie "Café Society."
-
E.
Justin Furstenfeld
Justin Furstenfeld is an American singer, songwriter, and guitarist best known as the lead vocalist and primary lyricist of the rock band Blue October.
- F. None of above. chosen
Provenance (5 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_69e0c45e5b8881908ac18fc2f493b114 |
completed | April 16, 2026, 11:13 a.m. |
| NER | Named-entity recognition | batch_69ee9d0e5a9c8190894ec3666d3296aa |
completed | April 26, 2026, 11:17 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_6a0a0f82f3508190bf0e4840a906526a |
completed | May 17, 2026, 6:57 p.m. |
| NEDg | Description generation | batch_6a0a102f488c8190ba1c4c0bddcfb4b3 |
completed | May 17, 2026, 6:59 p.m. |
| NED2 | Entity disambiguation (via description) | batch_6a0a10c8c5bc8190add0ee63eb338964 |
completed | May 17, 2026, 7:02 p.m. |
Created at: April 16, 2026, 6:27 p.m.