Triple
T14065222
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Bulletproof Monk |
E338450
|
entity |
| Predicate | producer |
P490
|
FINISHED |
| Object | Douglas Segal |
E338450
|
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: Douglas Segal | Statement: [Bulletproof Monk, producer, Douglas Segal]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Douglas Segal Context triple: [Bulletproof Monk, producer, Douglas Segal]
-
A.
Douglas Segal
chosen
Douglas Segal is a film producer best known for his work on the action-comedy movie "Bulletproof Monk."
-
B.
Philip Segal
Philip Segal is a television producer best known for his work on genre and reality-based series, including serving as an executive producer on the darkly comedic show "1000 Ways to Die."
-
C.
Steven Fierberg
Steven Fierberg is an American cinematographer known for his work on feature films and television series, including the romantic drama "Love & Other Drugs."
-
D.
J. David Siegel
J. David Siegel is a film editor known for his work on major animated features, including the superhero comedy "DC League of Super-Pets."
-
E.
Warren Goldstein
Warren Goldstein is a writer and scholar best known for co-authoring the popular science book "Longing for the Harmonies," which explores modern physics for a general audience.
- 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_69d81c67ba6c819091935650dfb3b895 |
completed | April 9, 2026, 9:38 p.m. |
| NER | Named-entity recognition | batch_69de5689c7f48190a47ca94eaa8a9ef9 |
completed | April 14, 2026, 3 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_6a008a1d8e088190a2168952ab5dc687 |
completed | May 10, 2026, 1:37 p.m. |
Created at: April 9, 2026, 10:21 p.m.