Triple

T817636
Position Surface form Disambiguated ID Type / Status
Subject Southampton E17684 entity
Predicate hasAirport P105 FINISHED
Object Southampton Airport E61566 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: Southampton Airport | Statement: [Southampton, hasAirport, Southampton Airport]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Southampton Airport
Context triple: [Southampton, hasAirport, Southampton Airport]
  • A. Southampton Airport chosen
    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.
  • B. Bristol Airport
    Bristol Airport is a major regional airport in South West England serving domestic and international flights, notably as a key base for low-cost carriers like easyJet.
  • C. Southend Airport
    Southend Airport is a regional international airport in Essex, England, serving the London area with passenger and cargo flights.
  • D. Manchester Airport
    Manchester Airport is a major international airport in North West England serving the Greater Manchester region and acting as a key hub for domestic and global flights.
  • E. Gatwick Airport
    Gatwick Airport is a major international airport serving the London area and is one of the busiest airports in the United Kingdom.
  • 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_69a4937bcaac8190a322524ac6f45a5a completed March 1, 2026, 7:28 p.m.
NER Named-entity recognition batch_69a4ab63f4a48190a61a14c3c41ed641 completed March 1, 2026, 9:11 p.m.
NED1 Entity disambiguation (via context triple) batch_69ac427fffe88190b28bd1b660bb90fe completed March 7, 2026, 3:21 p.m.
Created at: March 1, 2026, 7:38 p.m.