Triple

T9499345
Position Surface form Disambiguated ID Type / Status
Subject 81-717/714 series E229094 entity
Predicate usedIn P98 FINISHED
Object Baku Metro E382528 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: Baku Metro | Statement: [81-717/714 series, usedIn, Baku Metro]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Baku Metro
Context triple: [81-717/714 series, usedIn, Baku Metro]
  • A. Baku Metro chosen
    Baku Metro is the rapid transit system serving Azerbaijan’s capital city, known for its Soviet-era architecture and role as a key component of Baku’s urban transportation network.
  • B. Tbilisi Metro
    Tbilisi Metro is the rapid transit system serving Georgia’s capital city, providing a primary backbone for urban public transportation.
  • C. Yerevan Metro
    Yerevan Metro is the rapid transit system serving Armenia’s capital city, providing underground rail transportation across key urban areas.
  • D. Tashkent Metro
    Tashkent Metro is the rapid transit system serving Uzbekistan’s capital, notable for its Soviet-era architecture and ornately decorated underground stations.
  • E. Ürümqi Metro
    Ürümqi Metro is the rapid transit system serving Ürümqi, the capital of China’s Xinjiang Uyghur Autonomous Region.
  • 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_69d13a0a5ec881908bb1643d2bea2c9f completed April 4, 2026, 4:19 p.m.
Created at: March 30, 2026, 7:56 p.m.