Triple

T9827939
Position Surface form Disambiguated ID Type / Status
Subject Hauge i Dalane E238704 entity
Predicate municipality P852 FINISHED
Object Sokndal E262270 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: Sokndal | Statement: [Hauge i Dalane, municipality, Sokndal]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Sokndal
Context triple: [Hauge i Dalane, municipality, Sokndal]
  • A. Sokndal chosen
    Sokndal is a coastal municipality in Rogaland county in southwestern Norway, known for its rugged coastline, historic settlements, and distinctive geological landscapes.
  • B. 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.
  • C. Sokna
    Sokna is an extinct Eastern Berber language formerly spoken around the oasis town of Sokna in central Libya.
  • D. Sunndalsøra
    Sunndalsøra is a village and industrial center in western Norway known for its aluminum production and dramatic fjord and mountain surroundings.
  • E. Slemdal
    Slemdal is a residential neighborhood in the Vestre Aker borough of Oslo, Norway, known for its green surroundings and affluent character.
  • 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_69ca84e0dd1881909800765d1e21f735 completed March 30, 2026, 2:12 p.m.
NER Named-entity recognition batch_69cdb324e7848190b9424a78ca653afe completed April 2, 2026, 12:07 a.m.
NED1 Entity disambiguation (via context triple) batch_69d269b54d04819096ddc9f16a6db17b completed April 5, 2026, 1:55 p.m.
Created at: March 30, 2026, 8:32 p.m.