Triple

T3496504
Position Surface form Disambiguated ID Type / Status
Subject Øresund Region E73863 entity
Predicate majorCity P316 FINISHED
Object Helsingør E270670 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: Helsingør | Statement: [Øresund Region, majorCity, Helsingør]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Helsingør
Context triple: [Øresund Region, majorCity, Helsingør]
  • A. Helsingør chosen
    Helsingør is a historic coastal city in eastern Denmark, best known internationally as the setting of Shakespeare’s Hamlet (as Elsinore) and for its prominent Kronborg Castle overlooking the Øresund Strait.
  • B. Nyborg
    Nyborg is a historic coastal town and former royal seat in central Denmark, located on the island of Funen.
  • C. Svendborg
    Svendborg is a historic coastal town and seaport in southern Denmark known for its maritime heritage and location on the island of Funen.
  • D. Herning
    Herning is a Danish city in the Central Jutland region known for its trade fairs, conference facilities, and vibrant cultural and sports events.
  • E. Horsens
    Horsens is a city in eastern Jutland, Denmark, known historically as a market and industrial town and as the birthplace of explorer Vitus Bering.
  • 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_69ad85cdb6e48190a335d412b9194ed8 completed March 8, 2026, 2:21 p.m.
NER Named-entity recognition batch_69adbbd16c0081908f13535f459618d1 completed March 8, 2026, 6:11 p.m.
NED1 Entity disambiguation (via context triple) batch_69b44ee6f0488190ab4a1c9065c48753 completed March 13, 2026, 5:52 p.m.
Created at: March 8, 2026, 3:18 p.m.