Triple

T9499343
Position Surface form Disambiguated ID Type / Status
Subject 81-717/714 series E229094 entity
Predicate usedIn P98 FINISHED
Object Kyiv Metro E98369 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: Kyiv Metro | Statement: [81-717/714 series, usedIn, Kyiv Metro]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Kyiv Metro
Context triple: [81-717/714 series, usedIn, Kyiv Metro]
  • A. Kyiv Metro chosen
    Kyiv Metro is the rapid transit system serving Ukraine’s capital, known for its deep underground stations and role as a major component of the city’s public transportation network.
  • B. Kharkiv Metro
    Kharkiv Metro is the rapid transit system serving the city of Kharkiv, Ukraine, providing urban rail transportation across multiple underground lines and stations.
  • C. Kyiv tram network
    The Kyiv tram network is an extensive urban light rail system in Ukraine’s capital, providing surface-level public transportation that complements the city’s metro and bus services.
  • D. Minsk Metro
    The Minsk Metro is a rapid transit system serving Belarus's capital city with multiple underground lines and stations.
  • E. Dynamo metro station
    Dynamo metro station is a Moscow Metro station on the Zamoskvoretskaya line, known for serving the VTB Arena and the surrounding sports complex area.
  • 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_69ca84753660819098e8d416e89e26ae completed March 30, 2026, 2:11 p.m.
NER Named-entity recognition batch_69cd983a94c48190a7ddf95a953c4ecc completed April 1, 2026, 10:12 p.m.
NED1 Entity disambiguation (via context triple) batch_69d12d412a008190adc82e1e3d56d107 completed April 4, 2026, 3:24 p.m.
Created at: March 30, 2026, 7:56 p.m.