Triple
T22706170
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Center-West |
E561458
|
entity |
| Predicate | hasCapitalCity |
P204
|
FINISHED |
| Object | Goiânia |
—
|
NE NERFINISHED |
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: Goiânia | Statement: [Center-West, hasCapitalCity, Goiânia]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Goiânia Context triple: [Center-West, hasCapitalCity, Goiânia]
-
A.
Goiânia
chosen
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.
Teresina
Teresina is the capital and largest city of the Brazilian state of Piauí, known for its hot climate and location near the confluence of the Parnaíba and Poti rivers.
-
C.
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.
-
D.
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.
-
E.
Dourados
Dourados is a major agricultural and commercial city in the Brazilian state of Mato Grosso do Sul, known as an important regional economic and educational center.
- F. None of above.
- G. Unsure - the case is ambiguous/there is not enough information to decide.
Provenance (2 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_69e2454f1348819088d83f420925a5c1 |
completed | April 17, 2026, 2:35 p.m. |
| NER | Named-entity recognition | batch_69f178ceba6c8190a538366a8e4648de |
completed | April 29, 2026, 3:19 a.m. |
Created at: April 17, 2026, 3:17 p.m.