Triple

T10462235
Position Surface form Disambiguated ID Type / Status
Subject Bamble E246703 entity
Predicate previousCounty P65436 FINISHED
Object Telemark E93796 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: Telemark | Statement: [Bamble, previousCounty, Telemark]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Telemark
Context triple: [Bamble, previousCounty, Telemark]
  • A. Telemark chosen
    Telemark is a historic region and former county in southeastern Norway known for its traditional folk culture, distinctive skiing heritage, and varied landscapes of mountains, forests, and coast.
  • B. Trysil
    Trysil is a Norwegian municipality renowned for its large alpine ski resort and extensive outdoor recreation opportunities.
  • C. Snåsa
    Snåsa is a rural municipality in Trøndelag county, Norway, known for its large lakes, forests, and strong South Sámi cultural heritage.
  • D. Finse
    Finse is a remote mountain village and railway station in Norway, known as the highest point on the Bergen Line and a popular base for hiking and glacier activities.
  • E. Bjørndal
    Bjørndal is a residential neighborhood in the Søndre Nordstrand borough of Oslo, Norway.
  • 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_69d381c16c248190a2fe5b471e584e9c completed April 6, 2026, 9:49 a.m.
NER Named-entity recognition batch_69d50884fac48190af22e181b1492557 completed April 7, 2026, 1:37 p.m.
NED1 Entity disambiguation (via context triple) batch_69d89fcc84b48190a39de0d9b9111ebd completed April 10, 2026, 6:59 a.m.
Created at: April 6, 2026, 12:19 p.m.