Triple
T13092491
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Mikel Arteta |
E310494
|
entity |
| Predicate | spouse |
P13
|
FINISHED |
| Object | Lorena Bernal |
E337485
|
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: Lorena Bernal | Statement: [Mikel Arteta, spouse, Lorena Bernal]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Lorena Bernal Context triple: [Mikel Arteta, spouse, Lorena Bernal]
-
A.
Lorena Bernal
chosen
Lorena Bernal is an Argentine-born Spanish actress, model, and former Miss Spain who has also worked as a television presenter.
-
B.
Sofía García
Sofía García is a notable individual distinguished enough to be specifically recognized as a prominent bearer of the García surname.
-
C.
Claudia Ramírez
Claudia Ramírez is a Mexican actress known for her work in film and television, particularly in acclaimed Mexican cinema of the late 20th century.
-
D.
Yalitza Aparicio
Yalitza Aparicio is a Mexican actress and former preschool teacher who gained international acclaim and an Academy Award nomination for her debut performance in Alfonso Cuarón’s film "Roma."
-
E.
Giovanna Ferrer
Giovanna Ferrer is the wife of Sean Hepburn Ferrer, the son of actress Audrey Hepburn and actor Mel Ferrer.
- 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_69d806a733548190989cfd4ce981ca33 |
completed | April 9, 2026, 8:05 p.m. |
| NER | Named-entity recognition | batch_69d9813acbac8190b2fe5e07287457cf |
completed | April 10, 2026, 11:01 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69f7396e6cf881908b4cc3836501ed08 |
completed | May 3, 2026, 12:02 p.m. |
Created at: April 9, 2026, 9:03 p.m.