Triple

T7372796
Position Surface form Disambiguated ID Type / Status
Subject County Dublin E170049 entity
Predicate hasAirport P105 FINISHED
Object Dublin Airport E28419 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: Dublin Airport | Statement: [County Dublin, hasAirport, Dublin Airport]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Dublin Airport
Context triple: [County Dublin, hasAirport, Dublin Airport]
  • A. Dublin Airport chosen
    Dublin Airport is Ireland’s busiest international airport, serving as a major European hub for passenger and low-cost airline traffic.
  • B. Cork Airport
    Cork Airport is an international airport in County Cork, Ireland, serving as a key regional gateway and a secondary hub for Aer Lingus.
  • C. Belfast International Airport
    Belfast International Airport is a major passenger and cargo airport in Northern Ireland, serving as one of the primary air travel hubs for the Belfast region and beyond.
  • D. Belfast City Airport
    Belfast City Airport is a regional airport serving Belfast, Northern Ireland, located close to the city centre and handling mainly domestic UK and short-haul European flights.
  • E. Terminal 1 (Dublin Airport)
    Terminal 1 at Dublin Airport is the older of the airport’s two main passenger terminals, handling a large share of short-haul and low-cost airline traffic.
  • 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_69c68a5bfaac81909ce7f001dfb70c76 completed March 27, 2026, 1:47 p.m.
NER Named-entity recognition batch_69c6f1a50898819087097a64e09e19eb completed March 27, 2026, 9:07 p.m.
NED1 Entity disambiguation (via context triple) batch_69c810de7618819099ab4ff328255d92 completed March 28, 2026, 5:33 p.m.
Created at: March 27, 2026, 3:07 p.m.