Triple

T6216550
Position Surface form Disambiguated ID Type / Status
Subject Rogaland E139000 entity
Predicate hasMunicipality P847 FINISHED
Object Tysvær
Tysvær is a coastal municipality in southwestern Norway known for its fjords, islands, and location between the cities of Haugesund and Stavanger.
E580448 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: Tysvær | Statement: [Rogaland, hasMunicipality, Tysvær]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Tysvær
Context triple: [Rogaland, hasMunicipality, Tysvær]
  • A. Svaneke
    Svaneke is a picturesque coastal town on the Danish island of Bornholm, known for its well-preserved half-timbered houses, harbor, and traditional smokehouses.
  • B. Kvænangen
    Kvænangen is a fjord in northern Norway known for its dramatic coastal scenery, rich marine life, and traditional fishing communities.
  • C. Vestre
    Vestre is a Norwegian surname most notably associated with Jan Christian Vestre, a prominent Norwegian politician and businessman.
  • D. Solør
    Solør is a traditional district in Eastern Norway known for its rural landscapes, forestry, and agriculture.
  • E. Trondenes
    Trondenes is a historic former municipality and parish in northern Norway, known for its medieval stone church and role as an administrative center in the Harstad region.
  • 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: Tysvær
Triple: [Rogaland, hasMunicipality, Tysvær]
Generated description
Tysvær is a coastal municipality in southwestern Norway known for its fjords, islands, and location between the cities of Haugesund and Stavanger.
NED2 Entity disambiguation (via description) gpt-5-mini-2025-08-07
Target entity: Tysvær
Target entity description: Tysvær is a coastal municipality in southwestern Norway known for its fjords, islands, and location between the cities of Haugesund and Stavanger.
  • A. Svaneke
    Svaneke is a picturesque coastal town on the Danish island of Bornholm, known for its well-preserved half-timbered houses, harbor, and traditional smokehouses.
  • B. Kvænangen
    Kvænangen is a fjord in northern Norway known for its dramatic coastal scenery, rich marine life, and traditional fishing communities.
  • C. Vestre
    Vestre is a Norwegian surname most notably associated with Jan Christian Vestre, a prominent Norwegian politician and businessman.
  • D. Solør
    Solør is a traditional district in Eastern Norway known for its rural landscapes, forestry, and agriculture.
  • E. Trondenes
    Trondenes is a historic former municipality and parish in northern Norway, known for its medieval stone church and role as an administrative center in the Harstad region.
  • 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_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_69c243e998e0819090a2162e2a0ab7b9 completed March 24, 2026, 7:57 a.m.
NEDg Description generation batch_69c245000c248190b097befc6e3e9909 completed March 24, 2026, 8:02 a.m.
NED2 Entity disambiguation (via description) batch_69c4fb839b2481909caa57f34a8837db completed March 26, 2026, 9:25 a.m.
Created at: March 22, 2026, 4:21 p.m.