Triple
T1258129
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Francis Ford Coppola |
E12438
|
entity |
| Predicate | relative |
P37
|
FINISHED |
| Object | Nicolas Cage |
E108795
|
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: Nicolas Cage | Statement: [Francis Ford Coppola, relative, Nicolas Cage]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Nicolas Cage Context triple: [Francis Ford Coppola, relative, Nicolas Cage]
-
A.
Nicolas Cage
chosen
Nicolas Cage is an American actor known for his intense and eclectic performances across action, drama, and independent films.
-
B.
Val Kilmer
Val Kilmer is an American actor known for his versatile performances in films such as "Top Gun," "The Doors," and "Batman Forever."
-
C.
Rob Lowe
Rob Lowe is an American actor known for his roles in films like "St. Elmo's Fire" and TV series such as "Parks and Recreation" and "9-1-1: Lone Star."
-
D.
Tim Roth
Tim Roth is an English actor known for his intense, often villainous roles in films such as "Reservoir Dogs," "Pulp Fiction," and "Rob Roy," as well as his collaborations with directors like Quentin Tarantino.
-
E.
Luke Goss
Luke Goss is an English actor and former drummer best known for his roles in genre films such as "Blade II" and "Hellboy II: The Golden Army."
- 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_69a4933352e08190ac617291985e76c0 |
completed | March 1, 2026, 7:27 p.m. |
| NER | Named-entity recognition | batch_69a4bfaa2b508190a3f61c67b3fa3ad4 |
completed | March 1, 2026, 10:37 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69acc61df4b48190aa142f30026e6580 |
completed | March 8, 2026, 12:43 a.m. |
Created at: March 1, 2026, 7:50 p.m.