Triple
T10638404
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Museo Evita |
E250651
|
entity |
| Predicate | dedicatedTo |
P500
|
FINISHED |
| Object | Eva Perón |
E477997
|
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: Eva Perón | Statement: [Museo Evita, dedicatedTo, Eva Perón]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Eva Perón Context triple: [Museo Evita, dedicatedTo, Eva Perón]
-
A.
Eva Perón
chosen
Eva Perón was the influential First Lady of Argentina, renowned for her championing of labor rights and social welfare and her enduring status as a populist and cultural icon.
-
B.
Isabel Perón
Isabel Perón is an Argentine politician who became the world's first female president, leading Argentina from 1974 to 1976 after the death of her husband Juan Domingo Perón.
-
C.
Agustina Castro
Agustina Castro is a member of the Castro family of Cuba, known primarily as a sister of revolutionary figures Fidel, Raúl, and Juanita Castro.
-
D.
Mirta Miller
Mirta Miller is an Argentine actress known for her work in film and television, particularly during the 1960s and 1970s.
-
E.
Máxima Zorreguieta Cerruti
Máxima Zorreguieta Cerruti is the Queen Máxima of the Netherlands, an Argentine-born royal known for her work in finance, microcredit, and global financial inclusion initiatives.
- 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_69d6aa5993448190a493b790b8f85010 |
completed | April 8, 2026, 7:19 p.m. |
| NER | Named-entity recognition | batch_69d6dfaf12188190a5774d4d64674653 |
completed | April 8, 2026, 11:07 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69d96bcd8c0c8190a0fad6a85b5604bb |
completed | April 10, 2026, 9:29 p.m. |
Created at: April 8, 2026, 9:04 p.m.