Triple

T1913713
Position Surface form Disambiguated ID Type / Status
Subject Zealand E38167 entity
Predicate contains P35 FINISHED
Object Slagelse E263377 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: Slagelse | Statement: [Zealand, contains, Slagelse]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Slagelse
Context triple: [Zealand, contains, Slagelse]
  • A. Slagelse chosen
    Slagelse is a town on the island of Zealand in Denmark known for its military presence, historical significance, and role as a regional commercial center.
  • B. Holbæk
    Holbæk is a coastal town and municipality in northwestern Zealand, Denmark, known for its harbor on Holbæk Fjord and role as a regional commercial and cultural center.
  • C. Vejle
    Vejle is a Danish city known for its scenic fjord setting, rolling hills, and role as a regional commercial and transportation hub in southeastern Jutland.
  • D. Næstved
    Næstved is a historic market town and commercial center in southern Denmark, located on the island of Zealand.
  • E. Kolding
    Kolding is a historic Danish city in Southern Jutland known for Koldinghus Castle, its fjord-side location, and its role as a regional cultural and educational center.
  • 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_69a8862a26088190aae5243695aeefc0 completed March 4, 2026, 7:21 p.m.
NER Named-entity recognition batch_69abb1e26b948190aa194c30755ac5df completed March 7, 2026, 5:04 a.m.
NED1 Entity disambiguation (via context triple) batch_69af5cb503bc8190823a843bb58d85e1 completed March 9, 2026, 11:50 p.m.
Created at: March 4, 2026, 7:35 p.m.