Triple
T23251469
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Roberto Marinho |
E581740
|
entity |
| Predicate | employer |
P7
|
FINISHED |
| Object | Grupo Globo |
E140862
|
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: Grupo Globo | Statement: [Roberto Marinho, employer, Grupo Globo]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Grupo Globo Context triple: [Roberto Marinho, employer, Grupo 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.
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.
-
D.
Mediaset
Mediaset is a major Italian commercial television and media company, founded by Silvio Berlusconi and known for operating several popular TV channels and media platforms.
-
E.
Grupo Editora Abril
Grupo Editora Abril is one of Brazil’s largest and most influential media and magazine publishing companies, known for producing a wide range of popular print and digital titles.
- 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_69e24606b17c81908aba1a4911c8a8ba |
completed | April 17, 2026, 2:39 p.m. |
| NER | Named-entity recognition | batch_69f193f7249481909424867e9542d35e |
completed | April 29, 2026, 5:15 a.m. |
| NED1 | Entity disambiguation (via context triple) | batch_6a0c3f67bf0c8190983d11c9866b6d53 |
completed | May 19, 2026, 10:45 a.m. |
Created at: April 17, 2026, 4:11 p.m.