Triple
T16333968
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | María Isabel Verdú Rollán |
E396627
|
entity |
| Predicate | alsoKnownAs |
P39
|
FINISHED |
| Object | Maribel Verdú |
E72383
|
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: Maribel Verdú | Statement: [María Isabel Verdú Rollán, alsoKnownAs, Maribel Verdú]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Maribel Verdú Context triple: [María Isabel Verdú Rollán, alsoKnownAs, 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.
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.
-
D.
Marta Curro
Marta Curro is an American former actress best known as the first wife of stage and screen actor Jerry Orbach.
-
E.
Blanca Parés
Blanca Parés is a Spanish actress best known for her role in Pedro Almodóvar’s acclaimed film "Julieta."
- 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_69d87f255b788190a400eba031dd85d8 |
completed | April 10, 2026, 4:40 a.m. |
| NER | Named-entity recognition | batch_69e2c4e1da1081909bec6e77e6109dce |
completed | April 17, 2026, 11:40 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_6a00580d372c81908fcc267cdc3812a7 |
completed | May 10, 2026, 10:03 a.m. |
Created at: April 10, 2026, 5:07 a.m.