Triple
T8085678
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | NYPD Red series |
E188724
|
entity |
| Predicate | coAuthor |
P398
|
FINISHED |
| Object |
Marshall Karp
Marshall Karp is an American novelist and screenwriter best known for co-authoring popular crime thrillers, including entries in the NYPD Red series.
|
E711719
|
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: Marshall Karp | Statement: [NYPD Red series, coAuthor, Marshall Karp]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Marshall Karp Context triple: [NYPD Red series, coAuthor, Marshall Karp]
-
A.
Allan Kayser
Allan Kayser is an American actor best known for playing Bubba Higgins on the sitcom "Mama’s Family."
-
B.
Aaron Kandell
Aaron Kandell is an American screenwriter best known for co-writing Disney's animated feature film "Moana."
-
C.
John C. Martin
John C. Martin was an American pharmaceutical executive and scientist best known for leading Gilead Sciences’ rise into a major biopharmaceutical company, particularly in antiviral and HIV/hepatitis C treatments.
-
D.
Larry Kaplan
Larry Kaplan is a pioneering video game designer and programmer best known as one of the co-founders of Activision and an early developer for the Atari 2600.
-
E.
Michael Berman
Michael Berman is a writer and contributor known for his work published in George magazine.
- 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: Marshall Karp Triple: [NYPD Red series, coAuthor, Marshall Karp]
Generated description
Marshall Karp is an American novelist and screenwriter best known for co-authoring popular crime thrillers, including entries in the NYPD Red series.
NED2
Entity disambiguation (via description)
gpt-5-mini-2025-08-07
Target entity: Marshall Karp Target entity description: Marshall Karp is an American novelist and screenwriter best known for co-authoring popular crime thrillers, including entries in the NYPD Red series.
-
A.
Allan Kayser
Allan Kayser is an American actor best known for playing Bubba Higgins on the sitcom "Mama’s Family."
-
B.
Aaron Kandell
Aaron Kandell is an American screenwriter best known for co-writing Disney's animated feature film "Moana."
-
C.
John C. Martin
John C. Martin was an American pharmaceutical executive and scientist best known for leading Gilead Sciences’ rise into a major biopharmaceutical company, particularly in antiviral and HIV/hepatitis C treatments.
-
D.
Larry Kaplan
Larry Kaplan is a pioneering video game designer and programmer best known as one of the co-founders of Activision and an early developer for the Atari 2600.
-
E.
Michael Berman
Michael Berman is a writer and contributor known for his work published in George magazine.
- 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_69ca82b662e88190b9323daab8c28a21 |
completed | March 30, 2026, 2:03 p.m. |
| NER | Named-entity recognition | batch_69cb415f73808190b69db386b447062e |
completed | March 31, 2026, 3:37 a.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69cc6402e41c819095442775938d4282 |
completed | April 1, 2026, 12:17 a.m. |
| NEDg | Description generation | batch_69cc68647cec81909736383fbe73d2e8 |
completed | April 1, 2026, 12:35 a.m. |
| NED2 | Entity disambiguation (via description) | batch_69cc69b93bbc8190be2338182dd57b17 |
completed | April 1, 2026, 12:41 a.m. |
Created at: March 30, 2026, 5:29 p.m.