Triple
T19646032
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Mimi Fariña |
E471672
|
entity |
| Predicate | familyName |
P18
|
FINISHED |
| Object | Fariña |
—
|
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: Fariña | Statement: [Mimi Fariña, familyName, Fariña]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Fariña Context triple: [Mimi Fariña, familyName, Fariña]
-
A.
Fariña
chosen
Fariña is the surname of American folk singer, songwriter, and activist Mimi Fariña, known for her musical work and social advocacy.
-
B.
Poleñino
Poleñino is a small municipality in the province of Huesca, Aragon, Spain, historically noted as the place where King Alfonso I of Aragon died.
-
C.
Frasqueira
Frasqueira is a premium category of Madeira wine denoting long-aged, high-quality vintage bottlings.
-
D.
Valdoviño
Valdoviño is a coastal municipality in the province of A Coruña, Galicia, Spain, known for its beaches and scenic Atlantic landscapes.
-
E.
Bisquera
Bisquera is the family name of Curt Bisquera, an American session drummer known for his work with numerous prominent artists.
- 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_69d8e51395348190ac1416d46dfc6db0 |
completed | April 10, 2026, 11:54 a.m. |
| NER | Named-entity recognition | batch_69e641250e108190a707452fefc87041 |
completed | April 20, 2026, 3:07 p.m. |
Created at: April 10, 2026, 1:44 p.m.