Triple

T2267349
Position Surface form Disambiguated ID Type / Status
Subject Moscow Central Diameters E50176 entity
Predicate connects P390 FINISHED
Object Moscow city center E222347 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: Moscow city center | Statement: [Moscow Central Diameters, connects, Moscow city center]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Moscow city center
Context triple: [Moscow Central Diameters, connects, Moscow city center]
  • A. Kitay-gorod chosen
    Kitay-gorod is a historic central district of Moscow known for its medieval walls, important government and commercial buildings, and proximity to Red Square and the Kremlin.
  • B. Krylatskoye
    Krylatskoye is a Moscow Metro station serving the Krylatskoye District in western Moscow, Russia.
  • C. Theatre Square, Moscow
    Theatre Square in Moscow is a historic central square renowned as a cultural hub, surrounded by landmark institutions including the Bolshoi Theatre.
  • D. Pushkino
    Pushkino is a town in Russia that serves as a suburban residential and industrial center northeast of Moscow.
  • E. Moscow Central Diameters
    Moscow Central Diameters is a system of suburban commuter rail lines in Moscow and the surrounding region that operates with metro-like frequency and integration into the city’s public transit network.
  • 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_69a88b01e0048190ba96431b5f990ba9 completed March 4, 2026, 7:41 p.m.
NER Named-entity recognition batch_69abc1baa0948190b07ffc347a4f714e completed March 7, 2026, 6:12 a.m.
NED1 Entity disambiguation (via context triple) batch_69af5cc87e3c8190832d6812a4282ed7 completed March 9, 2026, 11:50 p.m.
Created at: March 4, 2026, 7:48 p.m.