Triple

T13614434
Position Surface form Disambiguated ID Type / Status
Subject Bygland E325274 entity
Predicate containsSettlement P847 FINISHED
Object Byglandsfjord E1126363 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: Byglandsfjord | Statement: [Bygland, containsSettlement, Byglandsfjord]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Byglandsfjord
Context triple: [Bygland, containsSettlement, Byglandsfjord]
  • A. Byglandsfjorden chosen
    Byglandsfjorden is a long, narrow lake in Agder county in southern Norway, known for its scenic fjord-like landscape along the Otra river.
  • B. Båtsfjord
    Båtsfjord is a small fishing town and municipality in northeastern Norway, located on the Barents Sea coast of Finnmark.
  • C. Balsfjord
    Balsfjord is a fjord in northern Norway known for its scenic Arctic landscapes and proximity to the city of Tromsø.
  • D. Byfjorden
    Byfjorden is a coastal fjord in western Sweden known for its scenic waters and proximity to the town of Uddevalla.
  • E. Byfjorden
    Byfjorden is a coastal fjord in western Norway that forms the main seaway and natural harbor area adjacent to the city of Bergen.
  • 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_69d8076aae28819092cf636190ee5529 completed April 9, 2026, 8:09 p.m.
NER Named-entity recognition batch_69dbb0abe1208190a1e0a32dc141d836 completed April 12, 2026, 2:48 p.m.
NED1 Entity disambiguation (via context triple) batch_69fe7e70dc788190850278a40a5a62e4 completed May 9, 2026, 12:23 a.m.
Created at: April 9, 2026, 9:50 p.m.