Triple
T1198413
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | The Five-Year Engagement |
E25719
|
entity |
| Predicate | executiveProducer |
P7225
|
FINISHED |
| Object |
Nathan Kahane
Nathan Kahane is a film producer and studio executive known for backing numerous successful Hollywood comedies and genre films.
|
E136662
|
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: Nathan Kahane | Statement: [The Five-Year Engagement, executiveProducer, Nathan Kahane]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Nathan Kahane Context triple: [The Five-Year Engagement, executiveProducer, Nathan Kahane]
-
A.
Nathan Grossman
Nathan Grossman is a Swedish documentary filmmaker best known for directing the climate activist portrait film "I Am Greta."
-
B.
Josh Berman
Josh Berman is an American entrepreneur best known as a co-founder of the pioneering social networking site MySpace.
-
C.
Ryan Roslansky
Ryan Roslansky is the CEO of LinkedIn, known for leading the professional networking platform’s product and business strategy.
-
D.
Nathan Sugarman
Nathan Sugarman was an American physicist known for his work in nuclear chemistry and his contributions to the Manhattan Project.
-
E.
Jeremy Kleiner
Jeremy Kleiner is an American film producer known for his work on acclaimed films such as the civil rights drama "Selma."
- 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: Nathan Kahane Triple: [The Five-Year Engagement, executiveProducer, Nathan Kahane]
Generated description
Nathan Kahane is a film producer and studio executive known for backing numerous successful Hollywood comedies and genre films.
NED2
Entity disambiguation (via description)
gpt-5-mini-2025-08-07
Target entity: Nathan Kahane Target entity description: Nathan Kahane is a film producer and studio executive known for backing numerous successful Hollywood comedies and genre films.
-
A.
Nathan Grossman
Nathan Grossman is a Swedish documentary filmmaker best known for directing the climate activist portrait film "I Am Greta."
-
B.
Josh Berman
Josh Berman is an American entrepreneur best known as a co-founder of the pioneering social networking site MySpace.
-
C.
Ryan Roslansky
Ryan Roslansky is the CEO of LinkedIn, known for leading the professional networking platform’s product and business strategy.
-
D.
Nathan Sugarman
Nathan Sugarman was an American physicist known for his work in nuclear chemistry and his contributions to the Manhattan Project.
-
E.
Jeremy Kleiner
Jeremy Kleiner is an American film producer known for his work on acclaimed films such as the civil rights drama "Selma."
- 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_69a49429f5ec8190a6a205eb0ae81e5e |
completed | March 1, 2026, 7:31 p.m. |
| NER | Named-entity recognition | batch_69a4bd9c013c8190822d44d465d60fdb |
completed | March 1, 2026, 10:28 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69ac7658cae8819081da26480926ff83 |
completed | March 7, 2026, 7:02 p.m. |
| NEDg | Description generation | batch_69ac770141a88190b71552d46fb4d2ad |
completed | March 7, 2026, 7:05 p.m. |
| NED2 | Entity disambiguation (via description) | batch_69ac777a7768819098b9d4dd771a6750 |
completed | March 7, 2026, 7:07 p.m. |
Created at: March 1, 2026, 7:46 p.m.