Triple

T6038204
Position Surface form Disambiguated ID Type / Status
Subject Orkdalen E134474 entity
Predicate hasPart P35 FINISHED
Object Meldal E499195 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: Meldal | Statement: [Orkdalen, hasPart, Meldal]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Meldal
Context triple: [Orkdalen, hasPart, Meldal]
  • A. Meldal chosen
    Meldal was a former municipality in Trøndelag county, Norway, known for its rural communities and historical mining activities before being merged into Orkland.
  • B. Sagene
    Sagene is a central district in Oslo, Norway, known for its historic industrial heritage along the Akerselva river and its mix of old workers’ housing and modern urban development.
  • C. Mosvik
    Mosvik was a former municipality in Trøndelag county, Norway, known for its rural landscape and coastal location along the Trondheimsfjord.
  • D. Malangen
    Malangen is a prominent fjord in northern Norway known for its scenic coastal landscapes and proximity to the city of Tromsø in Troms county.
  • E. Stordal
    Stordal is a small village and former municipality in western Norway, known for its scenic fjord landscape and traditional Norwegian architecture.
  • 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_69c71a5979208190b3bedb6234181245 completed March 28, 2026, 12:01 a.m.
Created at: March 22, 2026, 4:08 p.m.