Triple

T5242707
Position Surface form Disambiguated ID Type / Status
Subject Rod Robbie E118381 entity
Predicate workLocation P7 FINISHED
Object Toronto E1525 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: Toronto | Statement: [Rod Robbie, workLocation, Toronto]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Toronto
Context triple: [Rod Robbie, workLocation, Toronto]
  • A. Toronto chosen
    Toronto is the largest city in Canada and a major cultural, financial, and media hub located in the province of Ontario.
  • B. Ottawa
    Ottawa are an Algonquian-speaking Indigenous people of North America historically known for their role in Great Lakes trade networks and resistance to European colonial expansion.
  • C. Ottawa
    Ottawa is the capital city of Canada, located in eastern Ontario along the Ottawa River and known for its federal government institutions, cultural landmarks, and bilingual character.
  • D. North York
    North York is a major district in the north end of Toronto, Ontario, known for its dense urban development, shopping centers, and mixed residential and commercial areas.
  • E. Wellington, Ontario
    Wellington, Ontario is a small lakeside community in Prince Edward County known for its wineries, beaches, and vibrant arts and culinary scene.
  • 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_69bd4468aacc8190a8196f71855cdf4f completed March 20, 2026, 12:58 p.m.
NER Named-entity recognition batch_69bd7b4c6fa8819099442b1b110e51fb completed March 20, 2026, 4:52 p.m.
NED1 Entity disambiguation (via context triple) batch_69befe5e0d4c819095ea8b185754394e completed March 21, 2026, 8:23 p.m.
Created at: March 20, 2026, 1:49 p.m.