Triple

T13117748
Position Surface form Disambiguated ID Type / Status
Subject Diego Lugano E311138 entity
Predicate club P8194 FINISHED
Object Cerro Porteño E244416 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: Cerro Porteño | Statement: [Diego Lugano, club, Cerro Porteño]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Cerro Porteño
Context triple: [Diego Lugano, club, Cerro Porteño]
  • A. Cerro Porteño chosen
    Cerro Porteño is one of Paraguay’s most popular and successful football clubs, best known for its intense rivalry with Club Olimpia in the Asunción derby.
  • B. Horizontina
    Horizontina is a municipality in the state of Rio Grande do Sul in southern Brazil, known as the birthplace of supermodel Gisele Bündchen.
  • C. Barracas
    Barracas is a traditional working-class neighborhood in Buenos Aires, Argentina, known for its historic architecture, industrial past, and strong local identity.
  • D. Platense
    Platense is an Argentine professional football club best known for competing in the country’s top divisions and developing notable coaches and players.
  • E. Indeval
    Indeval is Mexico’s central securities depository, responsible for the custody, settlement, and administration of securities traded in the Mexican financial market.
  • 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_69d806a872d08190a329806f8ff30df4 completed April 9, 2026, 8:06 p.m.
NER Named-entity recognition batch_69d98182011c8190a504678affbb7787 completed April 10, 2026, 11:02 p.m.
NED1 Entity disambiguation (via context triple) batch_69f6e284c3c881909d65e2ba89fbe7af completed May 3, 2026, 5:52 a.m.
Created at: April 9, 2026, 9:06 p.m.