Triple

T12759004
Position Surface form Disambiguated ID Type / Status
Subject Ontario Highway 404 E304938 entity
Predicate passesThrough P225 FINISHED
Object Aurora E99471 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: Aurora | Statement: [Ontario Highway 404, passesThrough, Aurora]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Aurora
Context triple: [Ontario Highway 404, passesThrough, Aurora]
  • A. Aurora chosen
    Aurora is a suburban town in central York Region, Ontario, known as an affluent residential community within the Greater Toronto Area.
  • B. Aurora
    Aurora is the sleeping princess from Disney's animated film "Sleeping Beauty," known for her grace, kindness, and iconic awakening by true love's kiss.
  • C. Aurora
    Aurora was a Russian protected cruiser famed for firing the symbolic shot that signaled the start of the October Revolution in 1917.
  • D. Aurora
    Aurora is a mystical and theosophical treatise by Jakob Böhme that explores the nature of God, creation, and spiritual rebirth through symbolic and visionary theology.
  • E. Aurora
    Aurora was an influential late-18th-century American newspaper edited by Benjamin Franklin Bache that was known for its strong Republican stance and criticism of Federalist policies.
  • 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_69d7bdf1fcd081909ffb0e0d6fa3a07d completed April 9, 2026, 2:55 p.m.
NER Named-entity recognition batch_69d96d8d3eb08190ae998df5cc6d9ba6 completed April 10, 2026, 9:37 p.m.
NED1 Entity disambiguation (via context triple) batch_69f67c9c93248190b77c7d229da64ffb completed May 2, 2026, 10:37 p.m.
Created at: April 9, 2026, 5:28 p.m.