Triple

T11370990
Position Surface form Disambiguated ID Type / Status
Subject Garðabær E269339 entity
Predicate hasTwinTown P919 FINISHED
Object Naestved E272601 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: Naestved | Statement: [Garðabær, hasTwinTown, Naestved]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Naestved
Context triple: [Garðabær, hasTwinTown, Naestved]
  • A. Næstved chosen
    Næstved is a historic market town and commercial center in southern Denmark, located on the island of Zealand.
  • B. Nakskov
    Nakskov is a historic port town in southern Denmark located on the island of Lolland, known for its maritime industry and coastal setting.
  • C. Vordingborg
    Vordingborg is a historic coastal town in southern Denmark known for the ruins of Vordingborg Castle and its prominent Goose Tower.
  • D. 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.
  • E. Hellebæk
    Hellebæk is a coastal town in northeastern Zealand, Denmark, known for its scenic setting near Helsingør and its historic industrial and residential architecture.
  • 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_69d6aacca1048190b39dbbc2174616fa completed April 8, 2026, 7:21 p.m.
NER Named-entity recognition batch_69d7ea8b196881909af9b138661e816d completed April 9, 2026, 6:06 p.m.
NED1 Entity disambiguation (via context triple) batch_69e603d2320c81909ed6946c7b7dfb36 completed April 20, 2026, 10:45 a.m.
Created at: April 8, 2026, 9:33 p.m.