Triple

T5965549
Position Surface form Disambiguated ID Type / Status
Subject Inderøy E132741 entity
Predicate borderedBy P224 FINISHED
Object Steinkjer E124933 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: Steinkjer | Statement: [Inderøy, borderedBy, Steinkjer]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Steinkjer
Context triple: [Inderøy, borderedBy, Steinkjer]
  • A. Steinkjer chosen
    Steinkjer is a town and municipality in central Norway that serves as an important regional center and administrative hub in Trøndelag county.
  • B. Skien
    Skien is a historic city in southern Norway known as the birthplace of playwright Henrik Ibsen and as a regional commercial and industrial center.
  • C. Tvedestrand
    Tvedestrand is a coastal town and municipality in southern Norway known for its wooden houses, maritime heritage, and picturesque archipelago.
  • D. Risør
    Risør is a small coastal town in southern Norway known for its well-preserved wooden houses, maritime heritage, and annual wooden boat festival.
  • E. Sogndal
    Sogndal is a village and municipality in Vestland county, Norway, known for its scenic fjord landscape, agriculture, and as a regional education and service center.
  • 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_69c0086c2364819091e9fe2f58fa2517 completed March 22, 2026, 3:19 p.m.
NER Named-entity recognition batch_69c03a3ca1dc819098cde8ae5ec1d845 completed March 22, 2026, 6:51 p.m.
NED1 Entity disambiguation (via context triple) batch_69c6e4036f2081909fa40e07d19291f2 completed March 27, 2026, 8:09 p.m.
Created at: March 22, 2026, 4:03 p.m.