Triple
T10752074
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Nurse Betty |
E253594
|
entity |
| Predicate | screenwriter |
P2831
|
FINISHED |
| Object |
James Flamberg
James Flamberg is a screenwriter best known for co-writing the dark comedy film "Nurse Betty."
|
E909745
|
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: James Flamberg | Statement: [Nurse Betty, screenwriter, James Flamberg]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: James Flamberg Context triple: [Nurse Betty, screenwriter, James Flamberg]
-
A.
Michael Filerman
Michael Filerman was an American television producer best known for developing and producing popular prime-time soap operas during the 1970s and 1980s.
-
B.
Nick Frenkel
Nick Frenkel is a television producer best known for his work as an executive producer on the long-running comedy series "It's Always Sunny in Philadelphia."
-
C.
Garth Drabinsky
Garth Drabinsky is a Canadian theatrical producer and former film executive best known for staging large-scale Broadway and international productions, including the musical "Ragtime."
-
D.
Michael Vavitch
Michael Vavitch was a silent-era film actor known for his role in the 1924 drama "The Red Lily."
-
E.
Eric Lamonsoff
Eric Lamonsoff is a bumbling yet big-hearted family man and close friend of Lenny Feder in the Grown Ups comedy film series.
- 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: James Flamberg Triple: [Nurse Betty, screenwriter, James Flamberg]
Generated description
James Flamberg is a screenwriter best known for co-writing the dark comedy film "Nurse Betty."
NED2
Entity disambiguation (via description)
gpt-5-mini-2025-08-07
Target entity: James Flamberg Target entity description: James Flamberg is a screenwriter best known for co-writing the dark comedy film "Nurse Betty."
-
A.
Michael Filerman
Michael Filerman was an American television producer best known for developing and producing popular prime-time soap operas during the 1970s and 1980s.
-
B.
Nick Frenkel
Nick Frenkel is a television producer best known for his work as an executive producer on the long-running comedy series "It's Always Sunny in Philadelphia."
-
C.
Garth Drabinsky
Garth Drabinsky is a Canadian theatrical producer and former film executive best known for staging large-scale Broadway and international productions, including the musical "Ragtime."
-
D.
Michael Vavitch
Michael Vavitch was a silent-era film actor known for his role in the 1924 drama "The Red Lily."
-
E.
Eric Lamonsoff
Eric Lamonsoff is a bumbling yet big-hearted family man and close friend of Lenny Feder in the Grown Ups comedy film series.
- 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_69d6aa5e51e8819095f06881cecf152e |
completed | April 8, 2026, 7:19 p.m. |
| NER | Named-entity recognition | batch_69d71dc184d0819085f8bc4edb034377 |
completed | April 9, 2026, 3:32 a.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69e482f327e48190ad087c232fd05609 |
completed | April 19, 2026, 7:23 a.m. |
| NEDg | Description generation | batch_69e48715bd2081908774d325db2b6dd5 |
completed | April 19, 2026, 7:41 a.m. |
| NED2 | Entity disambiguation (via description) | batch_69e4886c0da881909105b3a45e786ce9 |
completed | April 19, 2026, 7:46 a.m. |
Created at: April 8, 2026, 9:15 p.m.