Triple
T20413267
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Isabel Sarli |
E500642
|
entity |
| Predicate | name |
P16
|
FINISHED |
| Object | Isabel Sarli |
—
|
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: Isabel Sarli | Statement: [Isabel Sarli, name, Isabel Sarli]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Isabel Sarli Context triple: [Isabel Sarli, name, Isabel Sarli]
-
A.
Isabel Sarli
chosen
Isabel Sarli was an iconic Argentine actress and sex symbol best known for her starring roles in erotic films of the 1950s–1970s directed by Armando Bó.
-
B.
Claudia Villafañe
Claudia Villafañe is an Argentine businesswoman and television personality best known for her long-term marriage to football legend Diego Maradona and her role in managing aspects of his career and estate.
-
C.
Adriana Novelli
Adriana Novelli is an editor known for her work on the film "Two Women."
-
D.
Malena Alterio
Malena Alterio is an Argentine-Spanish actress best known for her work in Spanish television comedies and films.
-
E.
Salma Paralluelo
Salma Paralluelo is a Spanish professional footballer and former elite sprinter known for her explosive pace and impact as a forward for both club and the Spain women’s national team.
- 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_69e0b4a935588190b9446a99b37ced44 |
completed | April 16, 2026, 10:06 a.m. |
| NER | Named-entity recognition | batch_69e67a417f208190be9bc11650ee0a87 |
completed | April 20, 2026, 7:10 p.m. |
Created at: April 16, 2026, 11:30 a.m.