Triple

T8407950
Position Surface form Disambiguated ID Type / Status
Subject Diocese of Haderslev E198546 entity
Predicate seat P75 FINISHED
Object Haderslev E128727 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: Haderslev | Statement: [Diocese of Haderslev, seat, Haderslev]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Haderslev
Context triple: [Diocese of Haderslev, seat, Haderslev]
  • A. Haderslev chosen
    Haderslev is a historic town in southern Denmark known for its medieval cathedral, old town center, and role as a regional cultural and administrative hub.
  • B. Hellebæk
    Hellebæk is a coastal town in northeastern Zealand, Denmark, known for its scenic setting near Helsingør and its historic industrial and residential architecture.
  • C. Thisted
    Thisted is a coastal town and municipality in northwestern Jutland, Denmark, known for its scenic location by the Limfjord and its role as a regional commercial and cultural center.
  • D. Gladsaxe
    Gladsaxe is a municipality in the northern suburbs of Copenhagen, Denmark, known for its residential areas, green spaces, and role as part of the Greater Copenhagen urban region.
  • E. Næstved
    Næstved is a historic market town and commercial center in southern Denmark, located on the island of Zealand.
  • 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_69ca8310df9c8190b25f16161cca3e41 completed March 30, 2026, 2:05 p.m.
NER Named-entity recognition batch_69cb8315a8a8819097f6da11b909b527 completed March 31, 2026, 8:17 a.m.
NED1 Entity disambiguation (via context triple) batch_69d100a1ad688190b1a2fc91ce3dbdc3 completed April 4, 2026, 12:14 p.m.
Created at: March 30, 2026, 6:05 p.m.