Triple

T19366023
Position Surface form Disambiguated ID Type / Status
Subject Calle Real E484402 entity
Predicate hasNearbyLandmark P2064 FINISHED
Object Iloilo 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: Iloilo City Hall | Statement: [Calle Real, hasNearbyLandmark, Iloilo City Hall]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Iloilo City Hall
Context triple: [Calle Real, hasNearbyLandmark, Iloilo City Hall]
  • A. Iloilo City Hall chosen
    Iloilo City Hall is the main government building of Iloilo City in the Philippines, serving as the administrative center and seat of the city’s local government.
  • B. Cebu City Hall
    Cebu City Hall is the main government building and administrative center of Cebu City in the Philippines.
  • C. Baguio City Hall
    Baguio City Hall is the main government building and administrative center of Baguio City in the Philippines, housing the offices of the city mayor and other key local government departments.
  • D. Cavite City Hall
    Cavite City Hall is the main government building and administrative center of Cavite City in the Philippines.
  • E. Pangasinan Provincial Capitol
    The Pangasinan Provincial Capitol is the main seat of government of Pangasinan province in the Philippines, known for its historic and neoclassical architecture.
  • 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_69d8e8d305088190ad13571532aa454c completed April 10, 2026, 12:10 p.m.
NER Named-entity recognition batch_69e619ac26d4819095836d737b629cf1 completed April 20, 2026, 12:18 p.m.
Created at: April 10, 2026, 1:35 p.m.