Triple

T5956148
Position Surface form Disambiguated ID Type / Status
Subject Hovedstaden E132519 entity
Predicate contains P35 FINISHED
Object Frederiksberg E255466 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: Frederiksberg | Statement: [Hovedstaden, contains, Frederiksberg]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Frederiksberg
Context triple: [Hovedstaden, contains, Frederiksberg]
  • A. Frederiksberg chosen
    Frederiksberg is an affluent, centrally located municipality in Denmark that forms an enclave within the city of Copenhagen and is known for its parks, cultural institutions, and historic architecture.
  • B. Valby
    Valby is a district in Copenhagen, Denmark, known as an important local transport and residential area within the city.
  • C. Hellerup
    Hellerup is a suburban district just north of central Copenhagen, known for its affluent residential areas, seaside location, and role as a key transport and commercial hub.
  • D. Herlev
    Herlev is a suburban municipality and town in the Capital Region of Denmark, located just northwest of central Copenhagen.
  • E. Ballerup
    Ballerup is a suburban municipality near Copenhagen in eastern Denmark, known for its residential areas, business parks, and sports facilities.
  • 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_69c141370ae48190b7da53210fd27315 completed March 23, 2026, 1:33 p.m.
Created at: March 22, 2026, 4:02 p.m.