Triple

T15332251
Position Surface form Disambiguated ID Type / Status
Subject Lovatnet E366562 entity
Predicate hasNearbyMountain P651 FINISHED
Object Skåla E366564 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: Skåla | Statement: [Lovatnet, hasNearbyMountain, Skåla]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Skåla
Context triple: [Lovatnet, hasNearbyMountain, Skåla]
  • A. Skåla chosen
    Skåla is a prominent mountain in western Norway, renowned for its steep ascent from the fjord and its distinctive stone tower near the summit.
  • B. Skibotn
    Skibotn is a small village in northern Norway known for its clear skies and role as a center for astronomical observations.
  • C. Flaskebekk
    Flaskebekk is a small residential settlement and coastal area in Nesodden municipality in Viken county, Norway.
  • D. Øygardstøl
    Øygardstøl is a popular mountain lodge and trailhead in Norway that serves as the main starting point for hikes to the famous Kjeragbolten rock.
  • E. Örgryte
    Örgryte is a historic district in Gothenburg, Sweden, known for its residential areas, green spaces, and proximity to the city 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_69d85a121520819093dcce999fdefe1a completed April 10, 2026, 2:01 a.m.
NER Named-entity recognition batch_69e03e0268608190947a58f559a67717 completed April 16, 2026, 1:40 a.m.
NED1 Entity disambiguation (via context triple) batch_69fef8b2ea5c8190b6e5f3fcbd7c265f completed May 9, 2026, 9:04 a.m.
Created at: April 10, 2026, 3:17 a.m.