Triple
T5485908
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Blade (1998 film) |
E123579
|
entity |
| Predicate | producer |
P490
|
FINISHED |
| Object |
Robert Engelman
Robert Engelman is a film producer known for his work on major Hollywood genre films, including action, science fiction, and fantasy projects.
|
E530522
|
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: Robert Engelman | Statement: [Blade (1998 film), producer, Robert Engelman]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Robert Engelman Context triple: [Blade (1998 film), producer, Robert Engelman]
-
A.
Bob Engelman
Bob Engelman is a film producer best known for working on major Hollywood movies, including the hit comedy "The Mask."
-
B.
Jeffrey Auerbach
Jeffrey Auerbach is a film producer best known for his work on the stop-motion animated feature "Corpse Bride."
-
C.
Stephen Goldblatt
Stephen Goldblatt is a British cinematographer known for his work on major films such as Charlie Wilson's War, Batman Forever, and Lethal Weapon.
-
D.
Daniel Ullman
Daniel Ullman was an American screenwriter known for his work on mid-20th-century genre films, particularly Westerns and thrillers.
-
E.
Philip Brownstein
Philip Brownstein was a professional basketball coach best known for leading the early NBA-era Chicago Stags franchise.
- 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: Robert Engelman Triple: [Blade (1998 film), producer, Robert Engelman]
Generated description
Robert Engelman is a film producer known for his work on major Hollywood genre films, including action, science fiction, and fantasy projects.
NED2
Entity disambiguation (via description)
gpt-5-mini-2025-08-07
Target entity: Robert Engelman Target entity description: Robert Engelman is a film producer known for his work on major Hollywood genre films, including action, science fiction, and fantasy projects.
-
A.
Bob Engelman
Bob Engelman is a film producer best known for working on major Hollywood movies, including the hit comedy "The Mask."
-
B.
Jeffrey Auerbach
Jeffrey Auerbach is a film producer best known for his work on the stop-motion animated feature "Corpse Bride."
-
C.
Stephen Goldblatt
Stephen Goldblatt is a British cinematographer known for his work on major films such as Charlie Wilson's War, Batman Forever, and Lethal Weapon.
-
D.
Daniel Ullman
Daniel Ullman was an American screenwriter known for his work on mid-20th-century genre films, particularly Westerns and thrillers.
-
E.
Philip Brownstein
Philip Brownstein was a professional basketball coach best known for leading the early NBA-era Chicago Stags franchise.
- 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_69bd464a2d908190869324ce176779c8 |
completed | March 20, 2026, 1:06 p.m. |
| NER | Named-entity recognition | batch_69bd92625a50819088133641ed6f25a9 |
completed | March 20, 2026, 6:30 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69c02777c0908190a0aebbbca3b7b0a6 |
completed | March 22, 2026, 5:31 p.m. |
| NEDg | Description generation | batch_69c037b4e04881908d07e704f2a161bb |
completed | March 22, 2026, 6:40 p.m. |
| NED2 | Entity disambiguation (via description) | batch_69c0384d023081909cb0d4ba4b80c07e |
completed | March 22, 2026, 6:43 p.m. |
Created at: March 20, 2026, 2:10 p.m.