Triple
T15554682
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Goiás |
E370836
|
entity |
| Predicate | hasCity |
P316
|
FINISHED |
| Object |
Goiás (city)
Goiás (city) is a historic colonial town in central Brazil, renowned for its well-preserved architecture and status as a UNESCO World Heritage Site.
|
E1169219
|
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: Goiás (city) | Statement: [Goiás, hasCity, Goiás (city)]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Goiás (city) Context triple: [Goiás, hasCity, Goiás (city)]
-
A.
Goiânia
Goiânia is the capital and largest city of the Brazilian state of Goiás, known as a major regional center for agriculture, industry, and services in central Brazil.
-
B.
Aparecida de Goiânia
Aparecida de Goiânia is a major city in central Brazil, forming part of the metropolitan area of Goiânia in the state of Goiás.
-
C.
Garça
Garça is the Portuguese term for a heron, a long-legged wading bird commonly found near wetlands and waterways.
-
D.
Guarulhos
Guarulhos is a major city in the São Paulo metropolitan area of Brazil, known as an important industrial and logistics hub.
-
E.
Feira de Santana
Feira de Santana is a major commercial and transportation hub in northeastern Brazil and the second-largest city in the state of Bahia.
- 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: Goiás (city) Triple: [Goiás, hasCity, Goiás (city)]
Generated description
Goiás (city) is a historic colonial town in central Brazil, renowned for its well-preserved architecture and status as a UNESCO World Heritage Site.
NED2
Entity disambiguation (via description)
gpt-5-mini-2025-08-07
Target entity: Goiás (city) Target entity description: Goiás (city) is a historic colonial town in central Brazil, renowned for its well-preserved architecture and status as a UNESCO World Heritage Site.
-
A.
Goiânia
Goiânia is the capital and largest city of the Brazilian state of Goiás, known as a major regional center for agriculture, industry, and services in central Brazil.
-
B.
Aparecida de Goiânia
Aparecida de Goiânia is a major city in central Brazil, forming part of the metropolitan area of Goiânia in the state of Goiás.
-
C.
Garça
Garça is the Portuguese term for a heron, a long-legged wading bird commonly found near wetlands and waterways.
-
D.
Guarulhos
Guarulhos is a major city in the São Paulo metropolitan area of Brazil, known as an important industrial and logistics hub.
-
E.
Feira de Santana
Feira de Santana is a major commercial and transportation hub in northeastern Brazil and the second-largest city in the state of Bahia.
- 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_69ff67830b4c8190a8c3f2168d8c2ec7 |
completed | May 9, 2026, 4:57 p.m. |
| NEDg | Description generation | batch_69ff6883b5048190b64e4361bc89dd80 |
completed | May 9, 2026, 5:01 p.m. |
| NED2 | Entity disambiguation (via description) | batch_69ff6911a76c819088c8a86d2106b6c6 |
completed | May 9, 2026, 5:04 p.m. |
Created at: April 10, 2026, 4:09 a.m.