Triple
T5023758
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Belo Horizonte |
E112920
|
entity |
| Predicate | urbanPlanner |
P20715
|
FINISHED |
| Object |
Aarão Reis
Aarão Reis was a Brazilian engineer and urban planner best known for designing the original master plan of the city of Belo Horizonte.
|
E486138
|
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: Aarão Reis | Statement: [Belo Horizonte, urbanPlanner, Aarão Reis]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Aarão Reis Context triple: [Belo Horizonte, urbanPlanner, Aarão Reis]
-
A.
Mateus
Mateus is a Portuguese surname commonly borne by individuals such as Rui Mateus.
-
B.
Raimundo
Raimundo is a masculine given name of Spanish and Portuguese origin, related to the name Ramón and ultimately derived from the Germanic name Raymond.
-
C.
Sebastião
Sebastião is the Portuguese variant of the given name Sebastian, commonly used in Portuguese-speaking countries.
-
D.
Gregorio
Gregorio is a masculine given name of Latin origin, commonly used in Spanish and Italian-speaking cultures and derived from the name Gregory.
-
E.
Timoteo
Timoteo is a masculine given name, commonly used in Romance-language countries, derived from the biblical name Timothy.
- 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: Aarão Reis Triple: [Belo Horizonte, urbanPlanner, Aarão Reis]
Generated description
Aarão Reis was a Brazilian engineer and urban planner best known for designing the original master plan of the city of Belo Horizonte.
NED2
Entity disambiguation (via description)
gpt-5-mini-2025-08-07
Target entity: Aarão Reis Target entity description: Aarão Reis was a Brazilian engineer and urban planner best known for designing the original master plan of the city of Belo Horizonte.
-
A.
Mateus
Mateus is a Portuguese surname commonly borne by individuals such as Rui Mateus.
-
B.
Raimundo
Raimundo is a masculine given name of Spanish and Portuguese origin, related to the name Ramón and ultimately derived from the Germanic name Raymond.
-
C.
Sebastião
Sebastião is the Portuguese variant of the given name Sebastian, commonly used in Portuguese-speaking countries.
-
D.
Gregorio
Gregorio is a masculine given name of Latin origin, commonly used in Spanish and Italian-speaking cultures and derived from the name Gregory.
-
E.
Timoteo
Timoteo is a masculine given name, commonly used in Romance-language countries, derived from the biblical name Timothy.
- 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_69bd4435c2f48190be593158cbfcf8a3 |
completed | March 20, 2026, 12:57 p.m. |
| NER | Named-entity recognition | batch_69bd736852e88190b69d6561ca7604c3 |
completed | March 20, 2026, 4:18 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69be9286bb28819095ca0ec858061419 |
completed | March 21, 2026, 12:43 p.m. |
| NEDg | Description generation | batch_69be933f3ed08190a128c1b3c9b3b1c3 |
completed | March 21, 2026, 12:46 p.m. |
| NED2 | Entity disambiguation (via description) | batch_69be940b2eac819099001d403501afac |
completed | March 21, 2026, 12:50 p.m. |
Created at: March 20, 2026, 1:36 p.m.