Triple

T21545411
Position Surface form Disambiguated ID Type / Status
Subject Oslomarka E531610 entity
Predicate hasPart P35 FINISHED
Object Lillomarka NE NERFINISHED

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: Lillomarka | Statement: [Oslomarka, hasPart, Lillomarka]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Lillomarka
Context triple: [Oslomarka, hasPart, Lillomarka]
  • A. Lillomarka chosen
    Lillomarka is a forested recreational area in Oslo, Norway, popular for hiking, skiing, and outdoor activities.
  • B. Rimforsa
    Rimforsa is a small locality in Kinda Municipality in Östergötland County, Sweden.
  • C. Arboga
    Arboga is a historic small town in central Sweden known for its medieval heritage and well-preserved old town.
  • D. Jorsalle
    Jorsalle is a small village in Nepal’s Khumbu region that serves as a common stopover for trekkers on the route to Everest Base Camp.
  • E. Götene
    Götene is a small locality and municipality in western Sweden known for its rural landscape and proximity to the historic Kinnekulle plateau by Lake Vänern.
  • F. None of above.
  • G. Unsure - the case is ambiguous/there is not enough information to decide.

Provenance (2 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_69e0c45f17148190949c330ab9c27706 completed April 16, 2026, 11:13 a.m.
NER Named-entity recognition batch_69eeb58e38808190888f3501cf4fff7c completed April 27, 2026, 1:02 a.m.
Created at: April 16, 2026, 6:28 p.m.