Triple

T10905467
Position Surface form Disambiguated ID Type / Status
Subject Ba–Vi E257557 entity
Predicate shortNameOfClub P3776 FINISHED
Object Vitória E262167 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: Vitória | Statement: [Ba–Vi, shortNameOfClub, Vitória]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Vitória
Context triple: [Ba–Vi, shortNameOfClub, Vitória]
  • A. Vitória
    Vitória is the capital city of the Brazilian state of Espírito Santo, known for its coastal setting, port activities, and surrounding islands.
  • B. Vitória chosen
    Vitória is a traditional Brazilian football club from Salvador, Bahia, best known for its intense local rivalry with Esporte Clube Bahia in the Ba–Vi derby.
  • C. 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.
  • D. Limeira
    Limeira is a municipality in the interior of the Brazilian state of São Paulo, known for its industrial activity and history in the jewelry and citrus sectors.
  • E. Botucatu
    Botucatu is a municipality in southeastern Brazil known for its higher-education institutions, especially São Paulo State University (UNESP), and its surrounding sandstone cliffs and natural landscapes.
  • 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_69d6aa8550c8819095508a2ed9acf3db completed April 8, 2026, 7:20 p.m.
NER Named-entity recognition batch_69d770656c288190828e71600bb0acd4 completed April 9, 2026, 9:24 a.m.
NED1 Entity disambiguation (via context triple) batch_69e155454890819087028a72ac2be8de completed April 16, 2026, 9:31 p.m.
Created at: April 8, 2026, 9:22 p.m.