Triple

T17174715
Position Surface form Disambiguated ID Type / Status
Subject Downtown Transit Center E416828 entity
Predicate operator P179 FINISHED
Object METRO E349884 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: [Downtown Transit Center, operator, METRO]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: METRO
Context triple: [Downtown Transit Center, operator, METRO]
  • A. METRO chosen
    METRO is the public-facing brand name used by Metro Transit for its network of buses, trains, and other mass transportation services.
  • B. Metro S.A.
    Metro S.A. is the state-owned company responsible for managing and operating the Santiago Metro system in Chile’s capital city.
  • C. Metros
    Metros is the nickname historically used for the MetroStars, the former Major League Soccer team now known as the New York Red Bulls.
  • D. Cine Metro
    Cine Metro is a historic cinema located on Lima’s Plaza San Martín, known for its classic architecture and role in the city’s cultural life.
  • E. El Metro
    El Metro is the popular nickname for Estadio Metropolitano Roberto Meléndez, a major football stadium in Barranquilla, Colombia, known as the home of the Colombian national team.
  • 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_69d886d5f34c8190b24564dfaa63f3fb completed April 10, 2026, 5:12 a.m.
NER Named-entity recognition batch_69e3fc0c329081909f118bd4b7be8653 completed April 18, 2026, 9:47 p.m.
NED1 Entity disambiguation (via context triple) batch_6a0148435f6081909bfc6cc1ef59d971 completed May 11, 2026, 3:08 a.m.
Created at: April 10, 2026, 5:37 a.m.