Triple
T6606155
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Roberto Carlos |
E149123
|
entity |
| Predicate | memberOfSportsTeam |
P330
|
FINISHED |
| Object |
União São João
União São João is a Brazilian football club based in Araras, São Paulo, known for having developed and featured notable players such as Roberto Carlos.
|
E599707
|
NE FINISHED |
How this triple was built (4 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: União São João | Statement: [Roberto Carlos, memberOfSportsTeam, União São João]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: União São João Context triple: [Roberto Carlos, memberOfSportsTeam, União São João]
-
A.
Portuguesa Santista
Portuguesa Santista is a Brazilian football club based in Santos, São Paulo, known for its youth development and regional tradition.
-
B.
Mengão
Mengão is the popular nickname of Clube de Regatas do Flamengo, one of Brazil’s most successful and widely supported football clubs.
-
C.
Jaguariúna
Jaguariúna is a municipality in southeastern Brazil known for its agribusiness, technology industries, and popular rodeo festival.
-
D.
Dois Unidos
Dois Unidos is a neighborhood located in the city of Recife, in the state of Pernambuco, Brazil.
-
E.
Vitória de Santo Antão
Vitória de Santo Antão is a municipality in northeastern Brazil known for its sugarcane-based economy, cachaça production, and colonial-era heritage.
- F. None of above. chosen
- G. Unsure - the case is ambiguous/there is not enough information to decide.
NEDg
Description generation
gpt-5.1
Instruction
Generate a one-sentence description of the target entity. You are given a context triple in the form (subject, predicate, object), where the object is the target entity. # Instructions Use the triple to infer relevant information about the entity. Describe the entity based on what is most defining, well-known. Avoid repeating the information from the triple, unless really essential. # Response Format Return only the sentence: "Description: [one-sentence description of the target entity]"
Input
Entity: União São João Triple: [Roberto Carlos, memberOfSportsTeam, União São João]
Generated description
União São João is a Brazilian football club based in Araras, São Paulo, known for having developed and featured notable players such as Roberto Carlos.
NED2
Entity disambiguation (via description)
gpt-5-mini-2025-08-07
Target entity: União São João Target entity description: União São João is a Brazilian football club based in Araras, São Paulo, known for having developed and featured notable players such as Roberto Carlos.
-
A.
Portuguesa Santista
Portuguesa Santista is a Brazilian football club based in Santos, São Paulo, known for its youth development and regional tradition.
-
B.
Mengão
Mengão is the popular nickname of Clube de Regatas do Flamengo, one of Brazil’s most successful and widely supported football clubs.
-
C.
Jaguariúna
Jaguariúna is a municipality in southeastern Brazil known for its agribusiness, technology industries, and popular rodeo festival.
-
D.
Dois Unidos
Dois Unidos is a neighborhood located in the city of Recife, in the state of Pernambuco, Brazil.
-
E.
Vitória de Santo Antão
Vitória de Santo Antão is a municipality in northeastern Brazil known for its sugarcane-based economy, cachaça production, and colonial-era heritage.
- F. None of above. chosen
Provenance (5 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_69c687eaa7508190bb58ce2aa02039b3 |
completed | March 27, 2026, 1:36 p.m. |
| NER | Named-entity recognition | batch_69c6af143d5c8190b62602602510b1cb |
completed | March 27, 2026, 4:23 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69c6cbce25b481908d600d38d3c5b871 |
completed | March 27, 2026, 6:26 p.m. |
| NEDg | Description generation | batch_69c6cd0a98908190a5725c49bad7589d |
completed | March 27, 2026, 6:31 p.m. |
| NED2 | Entity disambiguation (via description) | batch_69c6cdcc10c08190aa98212bd17063a3 |
completed | March 27, 2026, 6:34 p.m. |
Created at: March 27, 2026, 1:57 p.m.