Triple

T5846488
Position Surface form Disambiguated ID Type / Status
Subject Northwestern Ontario E129724 entity
Predicate hasCity P316 FINISHED
Object Dryden E123216 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: Dryden | Statement: [Northwestern Ontario, hasCity, Dryden]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Dryden
Context triple: [Northwestern Ontario, hasCity, Dryden]
  • A. Dryden
    Dryden is a small village in Tompkins County, New York, known for its rural character and proximity to the city of Ithaca.
  • B. Dryden chosen
    Dryden is a small city in northwestern Ontario, Canada, known historically for its forestry and paper mill industries.
  • C. Dryden
    Dryden is a surname most famously associated with Ken Dryden, the Hall of Fame Canadian ice hockey goaltender and former politician.
  • D. John Dryden
    John Dryden was a leading 17th-century English poet, playwright, and critic who became the dominant literary figure of the Restoration era and the first official Poet Laureate of England.
  • E. Mr. Dryden
    Mr. Dryden is a British government official in the film "Lawrence of Arabia" who helps orchestrate T.E. Lawrence’s assignment in the Arab Revolt.
  • 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_69c0084bd31c8190a796bb6284845e83 completed March 22, 2026, 3:18 p.m.
NER Named-entity recognition batch_69c0351157508190a78d2a7141e0cee8 completed March 22, 2026, 6:29 p.m.
NED1 Entity disambiguation (via context triple) batch_69c0a1a9ffa881908b38eeddb411c4ab completed March 23, 2026, 2:12 a.m.
Created at: March 22, 2026, 3:55 p.m.