Triple
T12725186
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Vera Cruz (1954 film) |
E304085
|
entity |
| Predicate | starring |
P1507
|
FINISHED |
| Object | Sara Montiel |
E607157
|
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: Sara Montiel | Statement: [Vera Cruz (1954 film), starring, Sara Montiel]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Sara Montiel Context triple: [Vera Cruz (1954 film), starring, Sara Montiel]
-
A.
Sara Montiel
chosen
Sara Montiel was a celebrated Spanish actress and singer who became an international film star and cultural icon in the mid-20th century.
-
B.
Maribel Verdú
Maribel Verdú is a Spanish actress acclaimed for her work in films such as "Pan’s Labyrinth" and "Y Tu Mamá También."
-
C.
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."
-
D.
Ana Ayora
Ana Ayora is an American actress best known for her roles in films like "The Big Wedding" and appearances in television series such as "Bosch" and "In the Dark."
-
E.
Josefa Ferrer
Josefa Ferrer is an actress known for playing the character Maria.
- 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_69d7bdf084148190ab9d513dc0735af4 |
completed | April 9, 2026, 2:55 p.m. |
| NER | Named-entity recognition | batch_69d96415ebe48190ae935bc3a9b00f65 |
completed | April 10, 2026, 8:56 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69f67c85c6b88190bbdd94a43915a7a4 |
completed | May 2, 2026, 10:36 p.m. |
Created at: April 9, 2026, 5:25 p.m.