Triple
T23251519
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Marinho family |
E581741
|
entity |
| Predicate | associatedWith |
P37
|
FINISHED |
| Object | Rede Globo |
—
|
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: Rede Globo | Statement: [Marinho family, associatedWith, Rede Globo]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Rede Globo Context triple: [Marinho family, associatedWith, Rede Globo]
-
A.
Rede Globo
chosen
Rede Globo is Brazil’s largest television network and one of the biggest media companies in Latin America, known for its telenovelas, news programming, and major entertainment broadcasts.
-
B.
Globo
Globo is a footwear and accessories retail chain brand operated by the Canadian company Aldo Group.
-
C.
Globo.com
Globo.com is a major Brazilian internet portal and digital media platform associated with the Globo media conglomerate.
-
D.
Grupo Televisa
Grupo Televisa is a major Mexican multimedia mass media company and one of the largest producers of Spanish-language content in the world.
-
E.
Telefe
Telefe is a major Argentine free-to-air television network known for broadcasting popular entertainment programs, telenovelas, and reality shows nationwide.
- 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_69e24606b17c81908aba1a4911c8a8ba |
completed | April 17, 2026, 2:39 p.m. |
| NER | Named-entity recognition | batch_69f193f7249481909424867e9542d35e |
completed | April 29, 2026, 5:15 a.m. |
Created at: April 17, 2026, 4:11 p.m.