Triple
T23306500
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Lavinia Valbonesi |
E590453
|
entity |
| Predicate | associatedWith |
P37
|
FINISHED |
| Object | Daniel Noboa |
—
|
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: Daniel Noboa | Statement: [Lavinia Valbonesi, associatedWith, Daniel Noboa]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Daniel Noboa Context triple: [Lavinia Valbonesi, associatedWith, Daniel Noboa]
-
A.
Daniel Noboa
chosen
Daniel Noboa is an Ecuadorian politician and businessman who became one of the country's youngest presidents after winning the 2023 election.
-
B.
Álvaro Noboa
Álvaro Noboa is an Ecuadorian businessman and politician, known as one of the country’s wealthiest individuals and a frequent presidential candidate.
-
C.
Luis Noboa Naranjo
Luis Noboa Naranjo was a prominent Ecuadorian businessman and industrialist, widely regarded as one of the country’s most influential entrepreneurs of the 20th century.
-
D.
Manuel Lasso
Manuel Lasso is a Spanish-language author known for his literary and philosophical works.
-
E.
de Cevallos
de Cevallos is a Spanish surname historically associated with notable figures in Spain and its former colonies.
- 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_69e25d1c0ecc8190a355aa229f06d0e0 |
completed | April 17, 2026, 4:17 p.m. |
| NER | Named-entity recognition | batch_69f1972737c08190bd011776564c3861 |
completed | April 29, 2026, 5:29 a.m. |
Created at: April 17, 2026, 5:05 p.m.