Triple
T12159152
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | José Álvaro Osorio Balvín |
E289658
|
entity |
| Predicate | familyName |
P18
|
FINISHED |
| Object | Osorio Balvín |
E220152
|
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: Osorio Balvín | Statement: [José Álvaro Osorio Balvín, familyName, Osorio Balvín]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Osorio Balvín Context triple: [José Álvaro Osorio Balvín, familyName, Osorio Balvín]
-
A.
Osorio Balvín
chosen
Osorio Balvín is the surname of Colombian reggaeton singer and global Latin music star J Balvin.
-
B.
Elida Reyna
Elida Reyna is an American Tejano singer widely recognized for her influential role in modern Tejano music and multiple award-winning recordings.
-
C.
Dulce María Loynaz
Dulce María Loynaz was a renowned Cuban poet and writer, celebrated as one of the most important voices in 20th-century Cuban and Latin American literature.
-
D.
Mutya Orquia
Mutya Orquia is a Filipino child actress best known for her roles in popular Philippine television dramas and series.
-
E.
Isabel Guzmán
Isabel Guzmán is an American government official who serves as the Administrator of the U.S. Small Business Administration, overseeing federal support for small businesses and entrepreneurs.
- 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_69d6ab4c6710819097a9d228382dde43 |
completed | April 8, 2026, 7:23 p.m. |
| NER | Named-entity recognition | batch_69d915c277e481908351bf4e664dda42 |
completed | April 10, 2026, 3:22 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69f60a837a5881908c600be0be334269 |
completed | May 2, 2026, 2:30 p.m. |
Created at: April 8, 2026, 9:50 p.m.