Triple
T17615890
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Belén Rueda |
E429081
|
entity |
| Predicate | name |
P16
|
FINISHED |
| Object | Belén Rueda |
—
|
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: Belén Rueda | Statement: [Belén Rueda, name, Belén Rueda]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Belén Rueda Context triple: [Belén Rueda, name, Belén Rueda]
-
A.
Belén Rueda
chosen
Belén Rueda is a Spanish actress best known internationally for her leading roles in acclaimed horror and thriller films such as "The Orphanage" and "The Sea Inside."
-
B.
Belén Atienza
Belén Atienza is a Spanish film producer known for her work on acclaimed international films such as "The Impossible" and collaborations with director J.A. Bayona.
-
C.
Pilar Roldán
Pilar Roldán is a Mexican fencer best known for taking the Olympic Oath for athletes and winning a silver medal in women's foil at the 1968 Mexico City Games.
-
D.
María Arjona
María Arjona is a notable individual who carries the Arjona surname, recognized as one of its distinguished bearers.
-
E.
Bárbara Goenaga
Bárbara Goenaga is a Spanish actress known for her work in film and television, particularly within Basque and Spanish-language cinema.
- 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_69d889e1c6148190ba76241e74688f8b |
completed | April 10, 2026, 5:25 a.m. |
| NER | Named-entity recognition | batch_69e46d32991c81909801161b0a416c94 |
completed | April 19, 2026, 5:50 a.m. |
Created at: April 10, 2026, 5:51 a.m.