Triple
T9629225
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Jason Gould |
E232553
|
entity |
| Predicate | name |
P16
|
FINISHED |
| Object | Jason Gould |
E232553
|
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: Jason Gould | Statement: [Jason Gould, name, Jason Gould]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Jason Gould Context triple: [Jason Gould, name, Jason Gould]
-
A.
Jason Gould
chosen
Jason Gould is an American actor, director, and singer known for his roles in films like "Say Anything..." and for being the son of Barbra Streisand and Elliott Gould.
-
B.
Matt Gould
Matt Gould is a musician and vocalist known for performing the opening theme of the television series "Turn: Washington's Spies."
-
C.
Nick Gillard
Nick Gillard is a British stunt coordinator and fight choreographer best known for designing the iconic lightsaber duels in the Star Wars prequel trilogy.
-
D.
Jeff Nathanson
Jeff Nathanson is an American screenwriter and film director best known for writing high-profile Hollywood films such as "Catch Me If You Can," "The Terminal," and Disney's live-action "The Lion King."
-
E.
Geoff Pierson
Geoff Pierson is an American actor known for his work in television dramas and comedies, including prominent roles on shows like Dexter and Unhappily Ever After.
- 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_69ca848793ec8190a93a12383a754dc0 |
completed | March 30, 2026, 2:11 p.m. |
| NER | Named-entity recognition | batch_69cd9b00162481908f396f6b6e470d6c |
completed | April 1, 2026, 10:24 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69d1bcb3a1ec819099c8a222c01c9d65 |
completed | April 5, 2026, 1:36 a.m. |
Created at: March 30, 2026, 8:10 p.m.