Triple

T7531124
Position Surface form Disambiguated ID Type / Status
Subject Sochi International Airport E178024 entity
Predicate cityServed P82 FINISHED
Object Sochi E33306 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: Sochi | Statement: [Sochi International Airport, cityServed, Sochi]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Sochi
Context triple: [Sochi International Airport, cityServed, 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. Ekaterinodar
    Ekaterinodar, now known as Krasnodar, was a major city in southern Russia that served as an important political and military center in the Kuban region.
  • C. Sochi seaport
    Sochi seaport is a prominent Black Sea maritime hub in the Russian resort city of Sochi, known for its passenger terminals, yacht marina, and distinctive Stalinist-era architecture.
  • D. Luts’k
    Luts’k is a historic city in northwestern Ukraine, known as the administrative center of Volyn Oblast and for its well-preserved medieval castle.
  • 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_69c69f2acdbc8190b5a8320168c1d0ba completed March 27, 2026, 3:15 p.m.
NER Named-entity recognition batch_69c6f8217b1c8190b3db453cee0fc4fd completed March 27, 2026, 9:35 p.m.
NED1 Entity disambiguation (via context triple) batch_69c8614787988190bb5479677f8485d2 completed March 28, 2026, 11:16 p.m.
Created at: March 27, 2026, 3:47 p.m.