Triple

T6216537
Position Surface form Disambiguated ID Type / Status
Subject Rogaland E139000 entity
Predicate hasMunicipality P847 FINISHED
Object Eigersund E587421 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: Eigersund | Statement: [Rogaland, hasMunicipality, Eigersund]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Eigersund
Context triple: [Rogaland, hasMunicipality, Eigersund]
  • A. Haugesund
    Haugesund is a coastal city in southwestern Norway known for its maritime heritage, shipbuilding industry, and annual film and jazz festivals.
  • B. Nordfjordeid
    Nordfjordeid is a village in western Norway known as a regional center in Nordfjord and the birthplace of mathematician Sophus Lie.
  • C. Egersund chosen
    Egersund is a coastal town in southwestern Norway known for its fishing industry, historic wooden architecture, and scenic harbor.
  • D. Sunndalsøra
    Sunndalsøra is a village and industrial center in western Norway known for its aluminum production and dramatic fjord and mountain surroundings.
  • E. Bardufoss
    Bardufoss is a town in northern Norway known for its military base, including the main headquarters of the Norwegian Army in the region, and its nearby airport.
  • 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_69c008aecb0c81909984b48f733ce8ae completed March 22, 2026, 3:20 p.m.
NER Named-entity recognition batch_69c062a1eb3881908c7f735cf9c429ce completed March 22, 2026, 9:44 p.m.
NED1 Entity disambiguation (via context triple) batch_69c7d368daac8190b08158f7ea8102ac completed March 28, 2026, 1:11 p.m.
Created at: March 22, 2026, 4:21 p.m.