Triple

T5772149
Position Surface form Disambiguated ID Type / Status
Subject 2014 FIFA World Cup E127353 entity
Predicate hostCity P1798 FINISHED
Object Fortaleza E107118 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: Fortaleza | Statement: [2014 FIFA World Cup, hostCity, Fortaleza]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Fortaleza
Context triple: [2014 FIFA World Cup, hostCity, Fortaleza]
  • A. Fortaleza chosen
    Fortaleza is a large coastal city in northeastern Brazil known for its beaches, tourism, and role as the capital of the state of Ceará.
  • B. São Sebastião
    São Sebastião is a civil parish in the municipality of Ponta Delgada on São Miguel Island in Portugal’s Azores archipelago.
  • C. Jaboatão dos Guararapes
    Jaboatão dos Guararapes is a major coastal city in northeastern Brazil known for its historical significance in the Dutch-Portuguese conflicts and its integration into the metropolitan area of Recife.
  • D. Vitória de Santo Antão
    Vitória de Santo Antão is a municipality in northeastern Brazil known for its sugarcane-based economy, cachaça production, and colonial-era heritage.
  • E. Port of Salvador
    The Port of Salvador is a major Brazilian seaport and cargo hub on the Atlantic coast, serving as a key gateway for trade in northeastern 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_69c00834f6308190851b0abeddd8ed7e completed March 22, 2026, 3:18 p.m.
NER Named-entity recognition batch_69c029adda188190a5c26c363614145f completed March 22, 2026, 5:41 p.m.
NED1 Entity disambiguation (via context triple) batch_69c09809cfcc8190b4d55db4b74316c7 completed March 23, 2026, 1:31 a.m.
Created at: March 22, 2026, 3:50 p.m.