Triple
T21906108
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Ana Torrent |
E540942
|
entity |
| Predicate | name |
P16
|
FINISHED |
| Object | Ana Torrent |
—
|
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: Ana Torrent | Statement: [Ana Torrent, name, Ana Torrent]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Ana Torrent Context triple: [Ana Torrent, name, Ana Torrent]
-
A.
Ana Torrent
chosen
Ana Torrent is a Spanish actress best known for her acclaimed childhood performances in films like "The Spirit of the Beehive" and "Cría cuervos."
-
B.
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.
-
C.
Maribel Verdú
Maribel Verdú is a Spanish actress acclaimed for her work in films such as "Pan’s Labyrinth" and "Y Tu Mamá También."
-
D.
Paz Vega
Paz Vega is a Spanish actress known for her roles in films such as "Sex and Lucía," "Spanglish," and various international productions.
-
E.
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.
- 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_69e0c47b4e8c81908c8076eaa4c8e4f2 |
completed | April 16, 2026, 11:14 a.m. |
| NER | Named-entity recognition | batch_69f121d62a648190af7074251dc6a03a |
completed | April 28, 2026, 9:08 p.m. |
Created at: April 16, 2026, 7:36 p.m.