Triple

T6403240
Position Surface form Disambiguated ID Type / Status
Subject Shannon Airport E144113 entity
Predicate serves P98 FINISHED
Object Limerick E546042 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: Limerick | Statement: [Shannon Airport, serves, Limerick]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Limerick
Context triple: [Shannon Airport, serves, Limerick]
  • A. Limerick
    Limerick is a historic city in western Ireland known for its medieval architecture, riverside setting on the River Shannon, and rich cultural and literary heritage.
  • B. Limerick City chosen
    Limerick City is a historic city in western Ireland, known for its medieval architecture, strategic location on the River Shannon, and role in key events of Irish history.
  • C. Waterford
    Waterford is a small incorporated city located in Stanislaus County in California’s Central Valley.
  • D. Waterford
    Waterford is a small town and village in eastern New York State, known as the eastern terminus of the Erie Canal and its historic canal locks.
  • E. Waterford
    Waterford is a historic port city in southeast Ireland, renowned as the country’s oldest city and for its traditional crystal glassmaking.
  • 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_69c008dc56fc81908d43ffcc11d73bdd completed March 22, 2026, 3:21 p.m.
NER Named-entity recognition batch_69c068af3f448190a94ecd5109e9e8e4 completed March 22, 2026, 10:09 p.m.
NED1 Entity disambiguation (via context triple) batch_69c638a6e6248190bda7ad3fbd8f4746 completed March 27, 2026, 7:58 a.m.
Created at: March 22, 2026, 4:35 p.m.