Triple
T20493193
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Mi corazón es tuyo |
E502799
|
entity |
| Predicate | mainCharacter |
P1183
|
FINISHED |
| Object | Ana Leal |
—
|
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 Leal | Statement: [Mi corazón es tuyo, mainCharacter, Ana Leal]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Ana Leal Context triple: [Mi corazón es tuyo, mainCharacter, Ana Leal]
-
A.
Aleida Núñez
chosen
Aleida Núñez is a Mexican actress and singer best known for her roles in popular telenovelas.
-
B.
Ignacia Allamand
Ignacia Allamand is a Chilean actress known for her roles in both Latin American cinema and international horror and thriller films.
-
C.
Adela Garcia
Adela Garcia is a highly accomplished professional fitness competitor best known for her multiple Ms. Fitness Olympia titles.
-
D.
María Valenzuela
María Valenzuela is an Argentine actress known for her extensive work in television, film, and theater across several decades.
-
E.
Pilar Salazar
Pilar Salazar is a main supporting character in the teen drama series "Love, Victor," known as Victor's younger sister who navigates her own personal and family struggles.
- 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_69e0b4b0373881909dd3e9387f82eab4 |
completed | April 16, 2026, 10:06 a.m. |
| NER | Named-entity recognition | batch_69e69cbb3bd081909351525208b41bba |
completed | April 20, 2026, 9:38 p.m. |
Created at: April 16, 2026, 11:35 a.m.