Triple

T19198250
Position Surface form Disambiguated ID Type / Status
Subject Fannrem E470027 entity
Predicate hasMunicipality P847 FINISHED
Object Orkland NE NERFINISHED

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: Orkland | Statement: [Fannrem, hasMunicipality, Orkland]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Orkland
Context triple: [Fannrem, hasMunicipality, Orkland]
  • A. Orkland chosen
    Orkland is a municipality in central Norway known for its mix of coastal and inland landscapes, formed through the merger of several former municipalities in Trøndelag county.
  • B. Portlands
    Portlands is a residential suburb within Mitchells Plain, a large township on the Cape Flats in Cape Town, South Africa.
  • C. Oakland, Oregon
    Oakland, Oregon is a small historic city in southern Oregon known for its well-preserved 19th-century downtown and rural, agricultural surroundings.
  • D. Oakland
    Oakland is a small city in western Iowa, United States, known for its rural Midwestern character and local agricultural community.
  • E. Oakland
    Oakland is a neighborhood on Chicago’s South Side known for its historic residential architecture and proximity to the lakefront.
  • F. None of above.
  • G. Unsure - the case is ambiguous/there is not enough information to decide.

Provenance (2 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_69d8dd0ad9088190a173b32657ae2e7a completed April 10, 2026, 11:20 a.m.
NER Named-entity recognition batch_69e5f8a8daac8190b3558a1388596fb0 completed April 20, 2026, 9:58 a.m.
Created at: April 10, 2026, 12:07 p.m.