Triple

T17370890
Position Surface form Disambiguated ID Type / Status
Subject Hole E422310 entity
Predicate hasSettlement P1068 FINISHED
Object Sundvollen NE ONNED1

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: Sundvollen | Statement: [Hole, hasSettlement, Sundvollen]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Sundvollen
Context triple: [Hole, hasSettlement, Sundvollen]
  • A. Sundvollen chosen
    Sundvollen is a small village in Norway known for its scenic location by Tyrifjorden and as a gateway to popular hiking areas like Krokskogen and viewpoints such as Kongens utsikt.
  • B. Söll
    Söll is a popular Austrian village and ski resort in the Kitzbühel Alps, known for its extensive winter sports facilities and scenic alpine setting.
  • C. Høvelte
    Høvelte is a locality in Denmark known primarily for hosting a major Danish Army military barracks and training area.
  • D. Follebu
    Follebu is a village in Innlandet county, Norway, known for its rural setting and traditional Norwegian countryside character within Gausdal municipality.
  • E. Sulden
    Sulden is a small alpine village and ski resort in South Tyrol, northern Italy, known for its dramatic high-mountain scenery in the Ortler Alps.
  • 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_69d889d6535c81908be333c01deaec4e completed April 10, 2026, 5:25 a.m.
NER Named-entity recognition batch_69e43a68ff448190b505861e56df5b6d completed April 19, 2026, 2:14 a.m.
NED1 Entity disambiguation (via context triple) batch_6a019568a27c8190af1bbe6db75f3e6f in_progress May 11, 2026, 8:38 a.m.
Created at: April 10, 2026, 5:44 a.m.