Triple

T3071591
Position Surface form Disambiguated ID Type / Status
Subject Loblaws E64035 entity
Predicate competitor P1375 FINISHED
Object Metro E284690 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: Metro | Statement: [Loblaws, competitor, Metro]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Metro
Context triple: [Loblaws, competitor, Metro]
  • A. Metro
    Metro is the rapid transit system serving the Washington, D.C. metropolitan area, operated by the Washington Metropolitan Area Transit Authority (WMATA).
  • B. Metro
    Metro is the primary public transportation agency serving Los Angeles County, operating buses, light rail, subway, and other transit services across the region.
  • C. Metro
    "Metro" is a Russian disaster thriller film featuring Svetlana Khodchenkova in a prominent role, centered on a catastrophic flood in the Moscow subway system.
  • D. Metro chosen
    Metro is a multinational wholesale and food retail company headquartered in Germany, operating cash-and-carry stores and serving professional customers worldwide.
  • E. Metros
    Metros is the nickname historically used for the MetroStars, the former Major League Soccer team now known as the New York Red Bulls.
  • 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_69ad857a8aec8190bfdfd9c14554ac5a completed March 8, 2026, 2:19 p.m.
NER Named-entity recognition batch_69ada14c8bd881909cf1bb2649ba36db completed March 8, 2026, 4:18 p.m.
NED1 Entity disambiguation (via context triple) batch_69b1f8828c488190877902a6c2dfcb5e completed March 11, 2026, 11:19 p.m.
Created at: March 8, 2026, 3:02 p.m.