Triple
T21811725
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Goya en Burdeos |
E538489
|
entity |
| Predicate | stars |
P1956
|
FINISHED |
| Object | Maribel Verdú |
—
|
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: Maribel Verdú | Statement: [Goya en Burdeos, stars, Maribel Verdú]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Maribel Verdú Context triple: [Goya en Burdeos, stars, Maribel Verdú]
-
A.
Maribel Verdú
chosen
Maribel Verdú is a Spanish actress acclaimed for her work in films such as "Pan’s Labyrinth" and "Y Tu Mamá También."
-
B.
Ana Torrent
Ana Torrent is a Spanish actress best known for her acclaimed childhood performances in films like "The Spirit of the Beehive" and "Cría cuervos."
-
C.
Teresa Rabal
Teresa Rabal is a Spanish actress, singer, and television presenter best known for her work in children's entertainment and family-oriented shows.
-
D.
Sara Montiel
Sara Montiel was a celebrated Spanish actress and singer who became an international film star and cultural icon in the mid-20th century.
-
E.
Ana Valdés
Ana Valdés is a notable individual recognized for her contributions in her field, bearing the surname Valdés.
- 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_69e0c473f0f8819086c9d1b4a143bd67 |
completed | April 16, 2026, 11:13 a.m. |
| NER | Named-entity recognition | batch_69f07cc6cdf88190a31129acdc3bcec8 |
completed | April 28, 2026, 9:24 a.m. |
Created at: April 16, 2026, 6:53 p.m.