Triple

T5956150
Position Surface form Disambiguated ID Type / Status
Subject Hovedstaden E132519 entity
Predicate contains P35 FINISHED
Object Hillerød E95304 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: Hillerød | Statement: [Hovedstaden, contains, Hillerød]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Hillerød
Context triple: [Hovedstaden, contains, Hillerød]
  • A. Hillerød chosen
    Hillerød is a Danish town on the island of Zealand, known for the historic Frederiksborg Castle and its role as a regional administrative and cultural center.
  • B. Glostrup
    Glostrup is a suburban town and municipality in the Copenhagen metropolitan area of Denmark, known for its residential neighborhoods and commercial districts.
  • C. Rødovre
    Rødovre is a suburban municipality in the Capital Region of Denmark, located just west of central Copenhagen.
  • D. Herlev
    Herlev is a suburban municipality and town in the Capital Region of Denmark, located just northwest of central Copenhagen.
  • E. 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.
  • 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_69c0086b05cc8190a8f36a96927a525c completed March 22, 2026, 3:19 p.m.
NER Named-entity recognition batch_69c039c1de80819085c97a0aa2d37f32 completed March 22, 2026, 6:49 p.m.
NED1 Entity disambiguation (via context triple) batch_69c20d2e42c88190927bba51caec186f completed March 24, 2026, 4:03 a.m.
Created at: March 22, 2026, 4:02 p.m.