Triple
T23160263
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Álvaro Noboa |
E578561
|
entity |
| Predicate | employer |
P7
|
FINISHED |
| Object | Noboa Group |
—
|
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: Noboa Group | Statement: [Álvaro Noboa, employer, Noboa Group]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Noboa Group Context triple: [Álvaro Noboa, employer, Noboa Group]
-
A.
Noboa Group
chosen
Noboa Group is a major Ecuadorian agribusiness and trading conglomerate best known as one of the world’s leading banana producers and exporters.
-
B.
Patria Group
Patria Group is a Finnish defense, security, and aviation technology company known for developing and manufacturing military vehicles, systems, and related services.
-
C.
Grupo Anaya
Grupo Anaya is a major Spanish publishing group known for its extensive catalog of educational, literary, and reference books in the Spanish-speaking market.
-
D.
Grupo Carso
Grupo Carso is a major Mexican conglomerate controlled by Carlos Slim, with diversified interests spanning retail, industrial manufacturing, infrastructure, and real estate development.
-
E.
Miramar Group
Miramar Group is a Taiwanese conglomerate best known for its investments in retail, entertainment, and hospitality, including major shopping and leisure complexes.
- 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_69e245fc75348190a0288401044c8af8 |
completed | April 17, 2026, 2:38 p.m. |
| NER | Named-entity recognition | batch_69f18eff965081909aaa6fc1910293e2 |
completed | April 29, 2026, 4:54 a.m. |
Created at: April 17, 2026, 4:02 p.m.