Triple
T3228704
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Patricia Arquette |
E67684
|
entity |
| Predicate | spouse |
P13
|
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: [Patricia Arquette, spouse, Nicolas Cage]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Nicolas Cage Context triple: [Patricia Arquette, spouse, 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.
Edward Norton
Edward Norton is an acclaimed American actor and filmmaker known for his intense, nuanced performances in films such as "Fight Club," "American History X," and "Birdman."
-
D.
Tom Sizemore
Tom Sizemore was an American character actor known for his intense supporting roles in gritty war and crime films such as "Saving Private Ryan," "Heat," and "Black Hawk Down."
-
E.
Tim Matheson
Tim Matheson is an American actor and director best known for his roles in films like "National Lampoon's Animal House" and numerous television series.
- 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_69ad858c61888190a31196310d9b30b5 |
completed | March 8, 2026, 2:19 p.m. |
| NER | Named-entity recognition | batch_69adaeb6f8588190a33a9d6c779e8992 |
completed | March 8, 2026, 5:15 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69b262675b588190bcff98e7fa3a0c77 |
completed | March 12, 2026, 6:51 a.m. |
Created at: March 8, 2026, 3:08 p.m.