Triple

T23077985
Position Surface form Disambiguated ID Type / Status
Subject Burlington rail yard E575384 entity
Predicate locatedIn P40 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: [Burlington rail yard, locatedIn, Burlington]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Burlington
Context triple: [Burlington rail yard, locatedIn, Burlington]
  • A. Burlington
    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 chosen
    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_69e245be28d48190ad1348d5a73db37d completed April 17, 2026, 2:37 p.m.
NER Named-entity recognition batch_69f18c6455f48190b84eaecdead0d963 completed April 29, 2026, 4:43 a.m.
Created at: April 17, 2026, 3:56 p.m.