Triple
T13486427
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | The Whole Ten Yards |
E318515
|
entity |
| Predicate | screenwriter |
P2831
|
FINISHED |
| Object | George Gallo |
E427996
|
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: George Gallo | Statement: [The Whole Ten Yards, screenwriter, George Gallo]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: George Gallo Context triple: [The Whole Ten Yards, screenwriter, George Gallo]
-
A.
George Gallo
chosen
George Gallo is an American screenwriter and filmmaker best known for creating the characters behind the "Bad Boys" action-comedy film franchise.
-
B.
Arthur Gallucci
Arthur Gallucci was the husband of Hungarian-American socialite and actress Magda Gabor.
-
C.
Frank Galati
Frank Galati was an American director, adapter, and screenwriter known for his acclaimed stage and film adaptations of literary works.
-
D.
Donald Gennaro
Donald Gennaro is a lawyer representing InGen in the Jurassic Park franchise, known for his ill-fated visit to the dinosaur theme park.
-
E.
Sam Lombardo
Sam Lombardo is the charismatic high school guidance counselor at the center of the twisting sexual assault and conspiracy plot in the 1998 neo-noir thriller film "Wild Things."
- 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_69d806b6bfec819089222715b2e86c8e |
completed | April 9, 2026, 8:06 p.m. |
| NER | Named-entity recognition | batch_69dbaf3a15b48190b63fb59e926a97ae |
completed | April 12, 2026, 2:42 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69fdd5b543308190a86e715106641484 |
completed | May 8, 2026, 12:23 p.m. |
Created at: April 9, 2026, 9:42 p.m.