Triple
T21450322
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | King's Ransom |
E529189
|
entity |
| Predicate | cinematographyBy |
P1953
|
FINISHED |
| Object | David Franco |
—
|
NE NERFINISHED |
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 Franco | Statement: [King's Ransom, cinematographyBy, David Franco]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: David Franco Context triple: [King's Ransom, cinematographyBy, David Franco]
-
A.
David Franco
chosen
David Franco is a cinematographer known for his work on the film "Boycott."
-
B.
Dave Franco
Dave Franco is an American actor and filmmaker known for roles in films like "21 Jump Street," "Now You See Me," and "Neighbors."
-
C.
Mattias Ferrell
Mattias Ferrell is one of the sons of American actor and comedian Will Ferrell.
-
D.
Chris DiDomenico
Chris DiDomenico is a Canadian professional ice hockey forward known for his playmaking skills and for having played in both the NHL and various European leagues.
-
E.
T. J. Miller
T. J. Miller is an American actor and stand-up comedian known for his roles in films like "Deadpool" and the HBO series "Silicon Valley," as well as extensive voice work in animated movies.
- F. None of above.
- G. Unsure - the case is ambiguous/there is not enough information to decide.
Provenance (2 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_69e0c457579481909db68053ed99750c |
completed | April 16, 2026, 11:13 a.m. |
| NER | Named-entity recognition | batch_69e9e9d281c0819080c3f8a58947a115 |
completed | April 23, 2026, 9:43 a.m. |
Created at: April 16, 2026, 6:06 p.m.