Triple
T6910491
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Somewhere in Time |
E159918
|
entity |
| Predicate | producer |
P490
|
FINISHED |
| Object |
Stephen Deutsch
Stephen Deutsch is a film producer best known for his work on the romantic time-travel drama "Somewhere in Time."
|
E628077
|
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: Stephen Deutsch | Statement: [Somewhere in Time, producer, Stephen Deutsch]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Stephen Deutsch Context triple: [Somewhere in Time, producer, Stephen Deutsch]
-
A.
Stephen Deutsch
Stephen Deutsch is a film producer best known for his work on the 1983 sports drama "All the Right Moves" starring Tom Cruise.
-
B.
Adam Siegel
Adam Siegel is a film producer known for his work on action and genre movies, including the 2008 thriller "Wanted."
-
C.
Jonathan Katz
Jonathan Katz is an American comedian, actor, and writer best known for co-creating and starring in the animated series "Dr. Katz, Professional Therapist."
-
D.
Douglas Meyer
Douglas Meyer is a theatrical producer best known for his work on the Broadway musical adaptation of "The Wedding Singer."
-
E.
Dan Goodman
Dan Goodman is a central character in the rock musical "Next to Normal," portrayed as a devoted husband and father struggling to hold his family together amid his wife's severe mental illness.
- 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: Stephen Deutsch Triple: [Somewhere in Time, producer, Stephen Deutsch]
Generated description
Stephen Deutsch is a film producer best known for his work on the romantic time-travel drama "Somewhere in Time."
NED2
Entity disambiguation (via description)
gpt-5-mini-2025-08-07
Target entity: Stephen Deutsch Target entity description: Stephen Deutsch is a film producer best known for his work on the romantic time-travel drama "Somewhere in Time."
-
A.
Stephen Deutsch
Stephen Deutsch is a film producer best known for his work on the 1983 sports drama "All the Right Moves" starring Tom Cruise.
-
B.
Adam Siegel
Adam Siegel is a film producer known for his work on action and genre movies, including the 2008 thriller "Wanted."
-
C.
Jonathan Katz
Jonathan Katz is an American comedian, actor, and writer best known for co-creating and starring in the animated series "Dr. Katz, Professional Therapist."
-
D.
Douglas Meyer
Douglas Meyer is a theatrical producer best known for his work on the Broadway musical adaptation of "The Wedding Singer."
-
E.
Dan Goodman
Dan Goodman is a central character in the rock musical "Next to Normal," portrayed as a devoted husband and father struggling to hold his family together amid his wife's severe mental illness.
- 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_69c68839ccb88190b4aa5cc1aca3448f |
completed | March 27, 2026, 1:38 p.m. |
| NER | Named-entity recognition | batch_69c6d9c00e948190b103a2b2a2738bb1 |
completed | March 27, 2026, 7:25 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69c749076f6c819088b0b40dd3e208b0 |
completed | March 28, 2026, 3:20 a.m. |
| NEDg | Description generation | batch_69c74c274258819099913ac5610730ac |
completed | March 28, 2026, 3:33 a.m. |
| NED2 | Entity disambiguation (via description) | batch_69c74cca47b88190867550802db43ef0 |
completed | March 28, 2026, 3:36 a.m. |
Created at: March 27, 2026, 2:25 p.m.