Triple

T6304174
Position Surface form Disambiguated ID Type / Status
Subject Vestre Aker E141330 entity
Predicate hasLandmark P105 FINISHED
Object Sørkedalen valley E585823 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: Sørkedalen valley | Statement: [Vestre Aker, hasLandmark, Sørkedalen valley]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Sørkedalen valley
Context triple: [Vestre Aker, hasLandmark, Sørkedalen valley]
  • A. Sørkedalen chosen
    Sørkedalen is a rural valley area in the northwest of Oslo, Norway, known for its forests, farms, and outdoor recreation opportunities.
  • B. Verdal valley
    Verdal valley is a fertile agricultural valley in Trøndelag county, central Norway, known for its farming landscape and the town of Verdalsøra.
  • C. Orkdalen
    Orkdalen is a valley and traditional district in central Norway known for the Orkla River and its agricultural landscapes within Trøndelag county.
  • D. Songdalen
    Songdalen is a former municipality in Agder county, Norway, now part of the city of Kristiansand and known for its rural landscapes and proximity to the Songdalselva river.
  • E. Groruddalen
    Groruddalen is a large valley and suburban area in the northeastern part of Oslo, Norway, known for its diverse population and extensive residential neighborhoods.
  • 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_69c008cf0ad4819095def81e2bd42f9f completed March 22, 2026, 3:20 p.m.
NER Named-entity recognition batch_69c0645f26a881909d5746151c0843cc completed March 22, 2026, 9:51 p.m.
NED1 Entity disambiguation (via context triple) batch_69c62d2cd75c81908961633a7ccf5dc9 completed March 27, 2026, 7:09 a.m.
Created at: March 22, 2026, 4:28 p.m.