Triple

T2419821
Position Surface form Disambiguated ID Type / Status
Subject Southend-on-Sea E53391 entity
Predicate servedBy P82 FINISHED
Object Southend Airport E16896 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: Southend Airport | Statement: [Southend-on-Sea, servedBy, Southend Airport]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Southend Airport
Context triple: [Southend-on-Sea, servedBy, Southend Airport]
  • A. Southend Airport chosen
    Southend Airport is a regional international airport in Essex, England, serving the London area with passenger and cargo flights.
  • B. Bournemouth Airport
    Bournemouth Airport is a regional international airport in southern England serving the town of Bournemouth and the surrounding Dorset and Hampshire areas.
  • C. Southampton Airport
    Southampton Airport is a regional international airport in Hampshire, England, serving the city of Southampton and the wider South East England area with domestic and European flights.
  • D. Luton Airport
    Luton Airport is a major international airport north of London that serves as a key hub for low-cost airlines and short-haul European flights.
  • E. Stansted Airport
    Stansted Airport is a major international airport serving the London area, particularly known as a hub for low-cost and European short-haul flights.
  • 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_69ab495c44d48190b7235b23719bc3f6 completed March 6, 2026, 9:38 p.m.
NER Named-entity recognition batch_69abc96e1b3881909de57501b5d4099a completed March 7, 2026, 6:45 a.m.
NED1 Entity disambiguation (via context triple) batch_69af98a342508190b30766327f298bf9 completed March 10, 2026, 4:05 a.m.
Created at: March 6, 2026, 9:42 p.m.