Triple

T18157320
Position Surface form Disambiguated ID Type / Status
Subject Leonardo Jardim E434665 entity
Predicate managedClub P3239 FINISHED
Object Beira-Mar 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: Beira-Mar | Statement: [Leonardo Jardim, managedClub, Beira-Mar]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Beira-Mar
Context triple: [Leonardo Jardim, managedClub, Beira-Mar]
  • A. Beira-Mar chosen
    Beira-Mar is a Portuguese football club based in Aveiro, known for competing in the country’s professional leagues and developing notable players such as Eusébio.
  • B. Lisbon–Guarda
    Lisbon–Guarda is a long-distance Intercidades rail service in Portugal connecting the capital city Lisbon with the inland city of Guarda.
  • C. Sertã
    Sertã is a municipality and town in central Portugal known for its forested landscapes, river beaches, and traditional cuisine.
  • D. Ria de Aveiro
    Ria de Aveiro is a coastal lagoon in central Portugal known for its canals, salt pans, and rich wetland biodiversity.
  • E. Portuguese Riviera
    The Portuguese Riviera is a glamorous coastal region west of Lisbon known for its historic seaside resorts, casinos, beaches, and affluent lifestyle.
  • 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_69d8b90b7a188190b3fc7b8d4a6cd20a completed April 10, 2026, 8:47 a.m.
NER Named-entity recognition batch_69e4debf43348190a22f23a4bbfab433 completed April 19, 2026, 1:55 p.m.
Created at: April 10, 2026, 10:30 a.m.