Triple

T20257647
Position Surface form Disambiguated ID Type / Status
Subject Fort Dupont E498745 entity
Predicate servedBy P82 FINISHED
Object Metrobus NE NERFINISHED

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: Metrobus | Statement: [Fort Dupont, servedBy, Metrobus]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Metrobus
Context triple: [Fort Dupont, servedBy, Metrobus]
  • A. Metrobus
    Metrobus is Istanbul’s bus rapid transit system that runs on dedicated lanes to provide fast, high-capacity public transportation across the city.
  • B. Metrobus
    Metrobus is Istanbul’s dedicated bus rapid transit system that runs on exclusive lanes to provide fast, high-capacity public transportation across the city.
  • C. Metrobus chosen
    Metrobus is the public bus transit system serving the Washington, D.C. metropolitan area, operated alongside the Metrorail network by the Washington Metropolitan Area Transit Authority (WMATA).
  • D. Metrobus
    Metrobus is Miami-Dade County’s primary public bus system, providing extensive local and regional transit service throughout the Greater Miami area.
  • E. Metrobus
    Metrobus is a British bus operator providing local and regional bus services, primarily in Southeast England.
  • F. None of above.
  • G. Unsure - the case is ambiguous/there is not enough information to decide.

Provenance (2 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_69da6275fa6c8190952924930adee150 completed April 11, 2026, 3:02 p.m.
NER Named-entity recognition batch_69e674c7296c819092860942de8f28d5 completed April 20, 2026, 6:47 p.m.
Created at: April 11, 2026, 11:41 p.m.