Triple

T22990168
Position Surface form Disambiguated ID Type / Status
Subject Mayor of Olinda E572023 entity
Predicate headquartersLocation P62 FINISHED
Object Olinda City Hall 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: Olinda City Hall | Statement: [Mayor of Olinda, headquartersLocation, Olinda City Hall]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Olinda City Hall
Context triple: [Mayor of Olinda, headquartersLocation, Olinda City Hall]
  • A. Olinda City Hall chosen
    Olinda City Hall is the main administrative building and seat of local government for the historic coastal city of Olinda in Brazil.
  • B. San Pablo City Hall
    San Pablo City Hall is the main municipal government building of San Pablo, California, housing city administrative offices and serving as the venue for official civic functions.
  • C. Fortaleza City Hall
    Fortaleza City Hall is the main administrative headquarters and executive center of the municipal government of Fortaleza, Brazil.
  • D. Panama City Hall
    Panama City Hall is the main administrative and governmental building serving as the headquarters of the municipal government of Panama City.
  • E. Recife City Hall
    Recife City Hall is the main municipal government building and administrative center of the city of Recife, Brazil.
  • 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_69e245b535808190adef8a9df3c584db completed April 17, 2026, 2:37 p.m.
NER Named-entity recognition batch_69f182ee3afc819099fbc6bef0b83bd5 completed April 29, 2026, 4:02 a.m.
Created at: April 17, 2026, 3:49 p.m.