Triple

T19923243
Position Surface form Disambiguated ID Type / Status
Subject Toronto–Niagara Falls corridor E478852 entity
Predicate includesCity P3207 FINISHED
Object Burlington 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: Burlington | Statement: [Toronto–Niagara Falls corridor, includesCity, Burlington]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Burlington
Context triple: [Toronto–Niagara Falls corridor, includesCity, Burlington]
  • A. Burlington chosen
    Burlington is a mid-sized city in southern Ontario, Canada, located on the shores of Lake Ontario between Toronto and Hamilton.
  • B. Burlington
    Burlington is a historic city in present-day New Jersey that once served as the colonial capital of the Province of New Jersey.
  • C. Burlington
    Burlington is a city in North Carolina known historically as a railroad and textile manufacturing hub in the Piedmont region of the state.
  • D. Burlington
    Burlington is a small city in northwestern Washington State known as a commercial hub for the surrounding Skagit Valley region.
  • E. Burlington
    Burlington is a small town located in Otsego County in central New York State, known for its rural character and scenic countryside.
  • 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_69d8e521855c8190b41871700afc8d6a completed April 10, 2026, 11:55 a.m.
NER Named-entity recognition batch_69e659c7be948190a65a1c78ba68dff3 completed April 20, 2026, 4:52 p.m.
Created at: April 10, 2026, 1:53 p.m.