Triple
T9983542
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Boomerang (1992 film) |
E196510
|
entity |
| Predicate | screenwriter |
P2831
|
FINISHED |
| Object | David Sheffield |
E335262
|
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: David Sheffield | Statement: [Boomerang (1992 film), screenwriter, David Sheffield]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: David Sheffield Context triple: [Boomerang (1992 film), screenwriter, David Sheffield]
-
A.
David Sheffield
chosen
David Sheffield is an American comedy writer best known for co-writing several Eddie Murphy films and contributing to classic Saturday Night Live sketches.
-
B.
Michael Wood
Michael Wood is a British historian and broadcaster known for his popular television documentaries and books on English history.
-
C.
Alan Fairford
Alan Fairford is a conscientious young Scottish lawyer who serves as one of the central protagonists in Sir Walter Scott’s novel "Redgauntlet."
-
D.
Graham Carr
Graham Carr is a Canadian academic and administrator who serves as the president of Concordia University in Montreal.
-
E.
David Magarshack
David Magarshack was a 20th-century British translator and biographer best known for his influential English translations of Russian classics, particularly the works of Dostoevsky.
- 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_69ca82efbce081908179b4b9c65096eb |
completed | March 30, 2026, 2:04 p.m. |
| NER | Named-entity recognition | batch_69cdb8bdc0388190bbbd4bdc5ac3adec |
completed | April 2, 2026, 12:30 a.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69d257f3c59481909b90896be0f3a870 |
completed | April 5, 2026, 12:39 p.m. |
Created at: March 30, 2026, 8:49 p.m.