Triple
T1876871
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | 2014 FIFA World Cup matches |
E39163
|
entity |
| Predicate | venueCity |
P19642
|
FINISHED |
| Object | Cuiabá |
E144203
|
NE FINISHED |
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: Cuiabá | Statement: [2014 FIFA World Cup matches, venueCity, Cuiabá]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Cuiabá Context triple: [2014 FIFA World Cup matches, venueCity, Cuiabá]
-
A.
Cuiabá
chosen
Cuiabá is the capital city of Brazil’s Mato Grosso state and a primary urban hub and access point for exploring the Pantanal wetlands.
-
B.
Magé
Magé is a municipality in the state of Rio de Janeiro, Brazil, located in the metropolitan region of Rio de Janeiro and known for its coastal setting and historical significance.
-
C.
Corumbá
Corumbá is a Brazilian city in the state of Mato Grosso do Sul, known as a key gateway to the Pantanal wetlands and an important regional center for river trade and ecotourism.
-
D.
Caxangá
Caxangá is a neighborhood and important urban area within the city of Recife, Brazil.
-
E.
Campo Grande
Campo Grande is a neighborhood in the city of Recife, Brazil.
- F. None of above.
- G. Unsure - the case is ambiguous/there is not enough information to decide.
Provenance (3 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_69a8862f7074819096afe7fe65e179e9 |
completed | March 4, 2026, 7:21 p.m. |
| NER | Named-entity recognition | batch_69abb0da543481908ab25806e6b80375 |
completed | March 7, 2026, 5 a.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69adeae44f6c8190a5924609863030a4 |
completed | March 8, 2026, 9:32 p.m. |
Created at: March 4, 2026, 7:34 p.m.