Triple

T19835100
Position Surface form Disambiguated ID Type / Status
Subject Odivelas, Portugal E476568 entity
Predicate hasAdministrativeDivision P747 FINISHED
Object Pontinha e Famões 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: Pontinha e Famões | Statement: [Odivelas, Portugal, hasAdministrativeDivision, Pontinha e Famões]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Pontinha e Famões
Context triple: [Odivelas, Portugal, hasAdministrativeDivision, Pontinha e Famões]
  • A. Pontinha chosen
    Pontinha is a civil parish in the municipality of Odivelas, within the Lisbon metropolitan area of Portugal.
  • B. Três Pontões
    Três Pontões is a locality in the Brazilian state of Espírito Santo, known for its rural landscape and proximity to distinctive rocky formations.
  • C. Bom Jardim
    Bom Jardim is a small municipality in the mountainous Região Serrana of Rio de Janeiro state in southeastern Brazil, known for its mild climate and rural landscapes.
  • D. Morrinhos
    Morrinhos is a municipality in the Brazilian state of Goiás, known for its agricultural economy and regional thermal springs.
  • E. Pinheiral
    Pinheiral is a small municipality in the state of Rio de Janeiro, Brazil, known for its rural character and growing role as a regional educational and residential center.
  • 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_69d8e51c7c188190b926f3a2a7b5f881 completed April 10, 2026, 11:55 a.m.
NER Named-entity recognition batch_69e656d0e738819093000d3307962328 completed April 20, 2026, 4:39 p.m.
Created at: April 10, 2026, 1:50 p.m.