Triple

T1201760
Position Surface form Disambiguated ID Type / Status
Subject Krasnodar Krai E25796 entity
Predicate hasResortCity P10436 FINISHED
Object Sochi E33306 NE FINISHED

How this triple was built (3 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: Sochi | Statement: [Krasnodar Krai, hasResortCity, Sochi]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Sochi
Context triple: [Krasnodar Krai, hasResortCity, Sochi]
  • A. Sochi chosen
    Sochi is a Russian resort city on the Black Sea coast, known for its subtropical climate, beaches, and as the host of the 2014 Winter Olympics.
  • B. Moscow
    Moscow is the capital and largest city of Russia, serving as its political, economic, and cultural center.
  • 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. Odintsovo
    Odintsovo is a town in western Russia that serves as an important suburban center just outside Moscow.
  • E. Khimki
    Khimki is a city in Moscow Oblast, Russia, forming part of the Moscow metropolitan area and known for its proximity to major transport hubs and industrial facilities.
  • F. None of above.
  • G. Unsure - the case is ambiguous/there is not enough information to decide.
PD Predicate disambiguation gpt-5-mini-2025-08-07
Target predicate: hasResortCity
Context triple: [Krasnodar Krai, hasResortCity, Sochi]
  • A. hasResortHotel
    Indicates that one entity owns, includes, or is associated with a resort hotel as part of its facilities or offerings.
  • B. hasTargetCity
    Indicates that something is directed toward, intended for, or specifically associated with a particular city as its target.
  • C. hasPopularResort chosen
    Indicates that a location or area contains or is associated with a resort that is widely visited or well-liked.
  • D. locatedInResortTown
    Indicates that something is situated within the boundaries of a town that is primarily known as a resort or vacation destination.
  • E. hasSisterResort
    Indicates that one resort is formally associated with another as its sister property, typically under common ownership or branding.
  • F. None of above.

Provenance (4 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_69a49429f5ec8190a6a205eb0ae81e5e completed March 1, 2026, 7:31 p.m.
NER Named-entity recognition batch_69a4bd9fece4819089a6a2d61e61fa2e completed March 1, 2026, 10:28 p.m.
NED1 Entity disambiguation (via context triple) batch_69ac831703bc8190839deb02075cb8fd completed March 7, 2026, 7:57 p.m.
PD Predicate disambiguation batch_69a4bb5ed2b88190aab992913957e1cf completed March 1, 2026, 10:19 p.m.
Created at: March 1, 2026, 7:46 p.m.