Triple
T1880998
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | J Balvin |
E39852
|
entity |
| Predicate | notableWork |
P4
|
FINISHED |
| Object | Blanco |
E173667
|
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: Blanco | Statement: [J Balvin, notableWork, Blanco]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Blanco Context triple: [J Balvin, notableWork, Blanco]
-
A.
Blanco
chosen
Blanco is a Spanish-language surname most notably associated with Mexican football legend and politician Cuauhtémoc Blanco.
-
B.
Blanc
Blanc is the surname of Mel Blanc, the legendary American voice actor best known for bringing to life many iconic Looney Tunes characters.
-
C.
Pulido
Pulido is a Spanish-language surname borne by various notable individuals in the arts, sports, and public life.
-
D.
Tinajo
Tinajo is a rural municipality on the western side of Lanzarote in Spain’s Canary Islands, known for its volcanic landscapes and proximity to Timanfaya National Park.
-
E.
Blau
The Blau is a small river in the German state of Baden-Württemberg that flows through the city of Blaustein before joining the Danube.
- 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_69a88633e4fc8190b7eb40463e048ec5 |
completed | March 4, 2026, 7:21 p.m. |
| NER | Named-entity recognition | batch_69abb0fb95b48190af5286662c8b9734 |
completed | March 7, 2026, 5 a.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69addf5c55e081909fc6912e1283a73a |
completed | March 8, 2026, 8:43 p.m. |
Created at: March 4, 2026, 7:34 p.m.