Triple

T17109850
Position Surface form Disambiguated ID Type / Status
Subject Государственное политическое управление E415196 entity
Predicate headquartersLocation P62 FINISHED
Object Москва E1747 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: Москва | Statement: [Государственное политическое управление, headquartersLocation, Москва]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Москва
Context triple: [Государственное политическое управление, headquartersLocation, Москва]
  • A. Moscow chosen
    Moscow is the capital and largest city of Russia, serving as its political, economic, and cultural center.
  • B. Moscow
    Moscow is a small borough in Lackawanna County, Pennsylvania, known as a residential community near the Scranton metropolitan area.
  • C. Moscow
    Moscow is a fictional character from the Spanish television series "Money Heist" (La Casa de Papel), known as a kind-hearted, blue-collar miner and the father of Denver who participates in the Royal Mint heist.
  • D. Moscow City
    Moscow City is a modern high-rise business district in western Moscow known for its cluster of skyscrapers, financial institutions, and commercial developments.
  • E. Mosca
    Mosca is the cunning and manipulative servant in Ben Jonson’s play "Volpone," known for orchestrating deceptions and driving much of the plot’s dark comedy.
  • 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_69d886d090cc8190a39cb94992586905 completed April 10, 2026, 5:12 a.m.
NER Named-entity recognition batch_69e3dc29c884819092a97d9663a1b1f7 completed April 18, 2026, 7:31 p.m.
NED1 Entity disambiguation (via context triple) batch_6a014145f7988190803d5c5e4f2705b0 completed May 11, 2026, 2:39 a.m.
Created at: April 10, 2026, 5:35 a.m.