Triple

T19008963
Position Surface form Disambiguated ID Type / Status
Subject Telemark county E465165 entity
Predicate containsMunicipality P852 FINISHED
Object Siljan 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: Siljan | Statement: [Telemark county, containsMunicipality, Siljan]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Siljan
Context triple: [Telemark county, containsMunicipality, Siljan]
  • A. Siljan
    Siljan is a lake in Telemark, Norway, known for its scenic surroundings and proximity to the town of Skien.
  • B. Siljan chosen
    Siljan is a small rural municipality in Telemark county, Norway, known for its forests, lakes, and outdoor recreation opportunities.
  • C. Siljan Ring
    Siljan Ring is a large ancient meteorite impact crater and lake system in central Sweden, known for its distinctive circular landscape and geological significance.
  • D. Arvidsjaur
    Arvidsjaur is a small town in northern Sweden known for its military presence, winter testing facilities, and proximity to Arctic wilderness.
  • E. Flemingsberg
    Flemingsberg is a district in the southern Stockholm urban area known for its major university campus, hospital, and commuter rail hub.
  • 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_69d8dd025c188190a1d81f5b4ec7e2c6 completed April 10, 2026, 11:20 a.m.
NER Named-entity recognition batch_69e5d6a72aa88190a04f13cd14ee77d4 completed April 20, 2026, 7:32 a.m.
Created at: April 10, 2026, 12:02 p.m.