Triple
T10514509
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Dave Franco |
E247997
|
entity |
| Predicate | birthName |
P65
|
FINISHED |
| Object | David John Franco |
E247997
|
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 John Franco | Statement: [Dave Franco, birthName, David John Franco]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: David John Franco Context triple: [Dave Franco, birthName, David John Franco]
-
A.
David Franco
David Franco is a cinematographer known for his work on the film "Boycott."
-
B.
Dave Franco
chosen
Dave Franco is an American actor and filmmaker known for roles in films like "21 Jump Street," "Now You See Me," and "Neighbors."
-
C.
James Franco
James Franco is an American actor, filmmaker, and academic known for his diverse roles in films like "127 Hours" and "Pineapple Express" and for his often experimental approach to art and performance.
-
D.
Nicholas John Frost
Nicholas John Frost is an English actor, comedian, and writer best known for his collaborations with Simon Pegg in films such as "Shaun of the Dead," "Hot Fuzz," and "The World's End."
-
E.
Joe Manganiello
Joe Manganiello is an American actor known for roles in projects like "True Blood," "Magic Mike," and various action films.
- 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_69d381c4aa948190942e1d803143fb0e |
completed | April 6, 2026, 9:49 a.m. |
| NER | Named-entity recognition | batch_69d509cade0c81908fcbd54a90106bf9 |
completed | April 7, 2026, 1:42 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69d94b13f4fc8190863d6e1aa7da5733 |
completed | April 10, 2026, 7:10 p.m. |
Created at: April 6, 2026, 12:27 p.m.