Triple
T5676469
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Entourage |
E125097
|
entity |
| Predicate | executiveProducer |
P7225
|
FINISHED |
| Object | Doug Ellin |
E538193
|
NE FINISHED |
How this triple was built (2 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: Doug Ellin | Statement: [Entourage, executiveProducer, Doug Ellin]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Doug Ellin Context triple: [Entourage, executiveProducer, Doug Ellin]
-
A.
Doug Ellin
chosen
Doug Ellin is an American screenwriter, director, and producer best known for creating the HBO comedy-drama series "Entourage."
-
B.
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.
-
C.
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.
-
D.
Adam Siegel
Adam Siegel is a film producer known for his work on action and genre movies, including the 2008 thriller "Wanted."
-
E.
Dan Pagis
Dan Pagis was a prominent Israeli poet, Holocaust survivor, and scholar whose innovative, allusive verse made him one of the central figures of modern Hebrew literature.
- F. None of above.
- G. Unsure - the case is ambiguous/there is not enough information to decide.
Provenance (3 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_69c008295c808190acfe78915e7d656a |
completed | March 22, 2026, 3:18 p.m. |
| NER | Named-entity recognition | batch_69c023728f488190a3622844d78caa13 |
completed | March 22, 2026, 5:14 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69c05a3211b08190868811db3d5268b1 |
completed | March 22, 2026, 9:08 p.m. |
Created at: March 22, 2026, 3:43 p.m.