Triple

T6038203
Position Surface form Disambiguated ID Type / Status
Subject Orkdalen E134474 entity
Predicate hasPart P35 FINISHED
Object Oppdal E128058 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: Oppdal | Statement: [Orkdalen, hasPart, Oppdal]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Oppdal
Context triple: [Orkdalen, hasPart, Oppdal]
  • A. Oppdal chosen
    Oppdal is a Norwegian mountain municipality and popular ski and outdoor recreation destination in central Norway.
  • B. Tvedestrand
    Tvedestrand is a coastal town and municipality in southern Norway known for its wooden houses, maritime heritage, and picturesque archipelago.
  • C. Steinkjer
    Steinkjer is a town and municipality in central Norway that serves as an important regional center and administrative hub in Trøndelag county.
  • D. Verdal
    Verdal is a municipality in central Norway known for its agricultural landscape, industrial activity, and the historic battlefield of Stiklestad.
  • E. Alvdal
    Alvdal is a rural municipality in Innlandet county, Norway, known for its agricultural landscape, outdoor recreation, and association with the author Kjell Aukrust.
  • 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_69c00875db5c819099dd5bb833ec43c2 completed March 22, 2026, 3:19 p.m.
NER Named-entity recognition batch_69c056ccac948190a27547878d4db8e4 completed March 22, 2026, 8:53 p.m.
NED1 Entity disambiguation (via context triple) batch_69c712707de88190b408ab01dd025954 completed March 27, 2026, 11:27 p.m.
Created at: March 22, 2026, 4:08 p.m.