Triple

T22905861
Position Surface form Disambiguated ID Type / Status
Subject Skegness railway station E568440 entity
Predicate stationCode P1289 FINISHED
Object SKG NE NERFINISHED

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: SKG | Statement: [Skegness railway station, stationCode, SKG]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: SKG
Context triple: [Skegness railway station, stationCode, SKG]
  • A. SKG chosen
    SKG is the three-letter IATA airport code for Thessaloniki Airport Makedonia in Greece.
  • B. Kose
    Kose is a settlement in northern Estonia known for lending its name to the historic Pirita-Kose-Kloostrimetsa motor racing circuit near Tallinn.
  • C. Skagen
    Skagen is a minimalist Danish-inspired watch and accessories brand known for its clean design aesthetic and modern, affordable timepieces.
  • D. Skagen
    Skagen is Denmark’s northernmost town, renowned for its picturesque fishing harbor, distinctive yellow houses, and the scenic meeting point of the North Sea and Baltic Sea.
  • E. SKW
    SKW is Poland’s Military Counterintelligence Service, responsible for protecting the armed forces and state defense structures from espionage, terrorism, and other security threats.
  • F. None of above.
  • G. Unsure - the case is ambiguous/there is not enough information to decide.

Provenance (2 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_69e2458cd9e48190943ad2e34485d939 completed April 17, 2026, 2:37 p.m.
NER Named-entity recognition batch_69f180198fe88190b2f8c2a827d95fdc completed April 29, 2026, 3:50 a.m.
Created at: April 17, 2026, 3:41 p.m.