Triple

T17134533
Position Surface form Disambiguated ID Type / Status
Subject Taaienberg E415801 entity
Predicate locatedInMunicipality P40 FINISHED
Object Maarkedal E204664 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: Maarkedal | Statement: [Taaienberg, locatedInMunicipality, Maarkedal]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Maarkedal
Context triple: [Taaienberg, locatedInMunicipality, Maarkedal]
  • A. Maarkedal chosen
    Maarkedal is a rural municipality in the Flemish Ardennes of East Flanders, Belgium, known for its hilly landscape and cycling routes.
  • B. Vildbjerg
    Vildbjerg is a Danish town that serves as the administrative center of the former Trehøje Municipality in the Central Denmark Region.
  • C. Birkelunden
    Birkelunden is a popular public park in Oslo’s Grünerløkka district, known for its green spaces, cultural events, and historic surroundings.
  • D. Ulriksdal
    Ulriksdal is a district in Solna, Sweden, known for the historic Ulriksdal Palace and its surrounding parklands along the Edsviken inlet.
  • E. Søndermarken
    Søndermarken is a historic public park in Copenhagen, Denmark, known for its wooded landscapes, walking paths, and proximity to Frederiksberg Gardens and the Copenhagen Zoo.
  • 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_69d886d15af4819092f92f8a129763e6 completed April 10, 2026, 5:12 a.m.
NER Named-entity recognition batch_69e3f02dca8881908efd73741397a207 completed April 18, 2026, 8:57 p.m.
NED1 Entity disambiguation (via context triple) batch_6a014150d63081908a5614f85694e57a completed May 11, 2026, 2:39 a.m.
Created at: April 10, 2026, 5:36 a.m.