Triple

T2673213
Position Surface form Disambiguated ID Type / Status
Subject Bangor International Airport E56396 entity
Predicate operator P179 FINISHED
Object City of Bangor E18442 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: City of Bangor | Statement: [Bangor International Airport, operator, City of Bangor]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: City of Bangor
Context triple: [Bangor International Airport, operator, City of Bangor]
  • A. Bangor
    Bangor is a historic cathedral city in northwest Wales, known for its university and scenic location near the Menai Strait.
  • B. Bangor metropolitan area
    The Bangor metropolitan area is a regional urban and economic hub in central-eastern Maine centered on the city of Bangor and its surrounding communities.
  • C. City of Pembroke
    The City of Pembroke is a small Canadian city on the Ottawa River in eastern Ontario, known as a regional service and commercial hub for the Ottawa Valley.
  • D. Bangor, Maine chosen
    Bangor, Maine is a small city in eastern Maine known as a regional commercial and cultural hub and famously associated with author Stephen King.
  • E. Bangor City Hall
    Bangor City Hall is the historic municipal government building and civic landmark located in downtown Bangor, Maine.
  • 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_69ab4a4b13fc81909dfdb3f23da46832 completed March 6, 2026, 9:42 p.m.
NER Named-entity recognition batch_69abd9b08b1c8190824342fc63e555d2 completed March 7, 2026, 7:54 a.m.
NED1 Entity disambiguation (via context triple) batch_69afa06170108190a6f4be82fa4ecd2a completed March 10, 2026, 4:38 a.m.
Created at: March 6, 2026, 9:54 p.m.