Triple

T6266775
Position Surface form Disambiguated ID Type / Status
Subject Lom, Norway E140432 entity
Predicate hasRiver P165 FINISHED
Object Bøvra
Bøvra is a river in Lom Municipality in Innlandet county, Norway, known for flowing through a mountainous valley landscape.
E585544 NE FINISHED

How this triple was built (4 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: Bøvra | Statement: [Lom, Norway, hasRiver, Bøvra]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Bøvra
Context triple: [Lom, Norway, hasRiver, Bøvra]
  • A. Bøelva
    Bøelva is a river in Telemark, Norway, known for flowing through the Bø area before emptying into the large lake Norsjø.
  • B. Brattvåg
    Brattvåg is a small coastal village in western Norway known for its maritime industry and scenic fjord landscape.
  • C. Finnvollheia
    Finnvollheia is a mountain that forms the highest point in the Fosen district of Trøndelag, Norway.
  • D. Bruhagen
    Bruhagen is a village and administrative center located on the island of Averøya in Møre og Romsdal county, Norway.
  • E. Snogebæk
    Snogebæk is a small coastal village and fishing hamlet on the Danish island of Bornholm, known for its harbor, beaches, and holiday atmosphere.
  • F. None of above. chosen
  • G. Unsure - the case is ambiguous/there is not enough information to decide.
NEDg Description generation gpt-5.1
Instruction
Generate a one-sentence description of the target entity. 
You are given a context triple in the form (subject, predicate, object), where the object is the target entity. 
# Instructions
Use the triple to infer relevant information about the entity. Describe the entity based on what is most defining, well-known. 
Avoid repeating the information from the triple, unless really essential.
# Response Format
Return only the sentence: "Description: [one-sentence description of the target entity]"
Input
Entity: Bøvra
Triple: [Lom, Norway, hasRiver, Bøvra]
Generated description
Bøvra is a river in Lom Municipality in Innlandet county, Norway, known for flowing through a mountainous valley landscape.
NED2 Entity disambiguation (via description) gpt-5-mini-2025-08-07
Target entity: Bøvra
Target entity description: Bøvra is a river in Lom Municipality in Innlandet county, Norway, known for flowing through a mountainous valley landscape.
  • A. Bøelva
    Bøelva is a river in Telemark, Norway, known for flowing through the Bø area before emptying into the large lake Norsjø.
  • B. Brattvåg
    Brattvåg is a small coastal village in western Norway known for its maritime industry and scenic fjord landscape.
  • C. Finnvollheia
    Finnvollheia is a mountain that forms the highest point in the Fosen district of Trøndelag, Norway.
  • D. Bruhagen
    Bruhagen is a village and administrative center located on the island of Averøya in Møre og Romsdal county, Norway.
  • E. Snogebæk
    Snogebæk is a small coastal village and fishing hamlet on the Danish island of Bornholm, known for its harbor, beaches, and holiday atmosphere.
  • F. None of above. chosen

Provenance (5 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_69c008cabc4081909723e2547c9d6cc0 completed March 22, 2026, 3:20 p.m.
NER Named-entity recognition batch_69c0639fdad081908492c44d369df8c5 completed March 22, 2026, 9:48 p.m.
NED1 Entity disambiguation (via context triple) batch_69c603ee891481909f640f54b70f9d60 completed March 27, 2026, 4:13 a.m.
NEDg Description generation batch_69c604a08f688190a34f0c3e37f50b3a completed March 27, 2026, 4:16 a.m.
NED2 Entity disambiguation (via description) batch_69c604f75848819094d2fb8d9faaa27e completed March 27, 2026, 4:17 a.m.
Created at: March 22, 2026, 4:25 p.m.