Triple
T15554681
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Goiás |
E370836
|
entity |
| Predicate | hasCity |
P316
|
FINISHED |
| Object |
Caldas Novas
Caldas Novas is a Brazilian resort city famous for its extensive natural hot springs and thermal tourism, located in the state of Goiás.
|
E1163943
|
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: Caldas Novas | Statement: [Goiás, hasCity, Caldas Novas]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Caldas Novas Context triple: [Goiás, hasCity, Caldas Novas]
-
A.
Barretos
Barretos is a municipality in the Brazilian state of São Paulo, widely known for hosting one of the largest annual rodeo festivals in Latin America.
-
B.
Pau dos Ferros
Pau dos Ferros is a municipality in the interior of Brazil’s Rio Grande do Norte state, known as a regional commercial and educational hub in the Alto Oeste Potiguar region.
-
C.
Vila de Rei
Vila de Rei is a small inland municipality in central Portugal known for its rural landscapes and its location near the country’s geodesic center.
-
D.
Sete Lagoas
Sete Lagoas is a city in the state of Minas Gerais, Brazil, known for its industrial activity and automotive manufacturing sector.
-
E.
Estância Velha
Estância Velha is a municipality in the state of Rio Grande do Sul in southern Brazil, known historically for its leather and footwear industry.
- 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: Caldas Novas Triple: [Goiás, hasCity, Caldas Novas]
Generated description
Caldas Novas is a Brazilian resort city famous for its extensive natural hot springs and thermal tourism, located in the state of Goiás.
NED2
Entity disambiguation (via description)
gpt-5-mini-2025-08-07
Target entity: Caldas Novas Target entity description: Caldas Novas is a Brazilian resort city famous for its extensive natural hot springs and thermal tourism, located in the state of Goiás.
-
A.
Barretos
Barretos is a municipality in the Brazilian state of São Paulo, widely known for hosting one of the largest annual rodeo festivals in Latin America.
-
B.
Pau dos Ferros
Pau dos Ferros is a municipality in the interior of Brazil’s Rio Grande do Norte state, known as a regional commercial and educational hub in the Alto Oeste Potiguar region.
-
C.
Vila de Rei
Vila de Rei is a small inland municipality in central Portugal known for its rural landscapes and its location near the country’s geodesic center.
-
D.
Sete Lagoas
Sete Lagoas is a city in the state of Minas Gerais, Brazil, known for its industrial activity and automotive manufacturing sector.
-
E.
Estância Velha
Estância Velha is a municipality in the state of Rio Grande do Sul in southern Brazil, known historically for its leather and footwear industry.
- 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_69d85cc6cf40819091f4a5facee1ebe6 |
completed | April 10, 2026, 2:13 a.m. |
| NER | Named-entity recognition | batch_69e04a96c0c88190808f68601a36b506 |
completed | April 16, 2026, 2:33 a.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69ff456209288190aba6debd434af741 |
completed | May 9, 2026, 2:32 p.m. |
| NEDg | Description generation | batch_69ff471cb68c8190924e894b190f15f4 |
completed | May 9, 2026, 2:39 p.m. |
| NED2 | Entity disambiguation (via description) | batch_69ff47aeddac8190a87024019ecb1396 |
completed | May 9, 2026, 2:41 p.m. |
Created at: April 10, 2026, 4:09 a.m.