Triple

T326271
Position Surface form Disambiguated ID Type / Status
Subject King of Ireland E6525 entity
Predicate capital P234 FINISHED
Object Dublin E9406 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 | Statement: [King of Ireland, capital, Dublin]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Dublin
Context triple: [King of Ireland, capital, Dublin]
  • A. Dublin chosen
    Dublin is the capital and largest city of Ireland, known for its rich literary heritage, historic architecture, and vibrant cultural and economic life.
  • B. Belfast
    Belfast is the capital and largest city of Northern Ireland, known for its historic shipbuilding industry, including the construction of the RMS Titanic, and its central role in the region’s political and cultural history.
  • C. Glasgow
    Glasgow is Scotland’s largest city, historically a major industrial and shipbuilding center, known for its rich cultural scene, distinctive architecture, and role as a key urban hub in the United Kingdom.
  • D. St John’s
    St John’s is a residential and commercial district within the town of Royal Tunbridge Wells in Kent, England.
  • E. Dublin Airport
    Dublin Airport is Ireland’s busiest international airport, serving as a major European hub for passenger 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_69a2e7933d6c8190bb2592ad13286ef2 completed Feb. 28, 2026, 1:03 p.m.
NER Named-entity recognition batch_69a2ea974d8481908c7d84f72a7728b6 completed Feb. 28, 2026, 1:16 p.m.
NED1 Entity disambiguation (via context triple) batch_69a3d241f924819087dedd32d7b6cc2b completed March 1, 2026, 5:44 a.m.
Created at: Feb. 28, 2026, 1:08 p.m.