Triple

T15947897
Position Surface form Disambiguated ID Type / Status
Subject Ullensvang Municipality E386733 entity
Predicate contains P35 FINISHED
Object Odda E365827 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: Odda | Statement: [Ullensvang Municipality, contains, Odda]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Odda
Context triple: [Ullensvang Municipality, contains, Odda]
  • A. Odda chosen
    Odda is a town in western Norway known for its dramatic fjord landscape, industrial heritage, and proximity to popular hiking destinations like Trolltunga.
  • B. Odensala
    Odensala is a locality within Östersund Municipality in Jämtland County, Sweden, functioning as a residential area near the city of Östersund.
  • C. Harestua
    Harestua is a village in Viken county, Norway, known for its residential community and proximity to the Harestua Solar Observatory.
  • D. Oederan
    Oederan is a small historic town in the Free State of Saxony in eastern Germany, known for its traditional architecture and model railway park.
  • E. Mora
    Mora is a canton in Costa Rica’s San José Province known for its rural landscapes, agricultural activities, and small-town communities.
  • 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_69d86da882448190a82ea962fe343b79 completed April 10, 2026, 3:25 a.m.
NER Named-entity recognition batch_69e156d2fda8819085279d2a0f8a02ab completed April 16, 2026, 9:38 p.m.
NED1 Entity disambiguation (via context triple) batch_69ffb5c0c8a481908aa7a40bca15e38e completed May 9, 2026, 10:31 p.m.
Created at: April 10, 2026, 4:53 a.m.