Triple

T3593275
Position Surface form Disambiguated ID Type / Status
Subject Kristiansund E76076 entity
Predicate composedOf P402 FINISHED
Object Innlandet
Innlandet is an island district of the Norwegian town of Kristiansund, known for its traditional wooden houses and coastal maritime character.
 E371974 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: Innlandet | Statement: [Kristiansund, composedOf, Innlandet]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07 
Target entity: Innlandet
Context triple: [Kristiansund, composedOf, Innlandet]
  • A. Innlandet
    Innlandet is a county in eastern Norway known for its inland landscapes, including mountains, forests, and important winter sports venues.
  • B. Hadeland
    Hadeland is a traditional rural district in southeastern Norway known for its agricultural landscape, historic churches, and the Hadeland Glassverk glassworks.
  • C. Numedal
    Numedal is a valley in southeastern Norway known for its traditional wooden architecture, medieval stave churches, and scenic river landscape.
  • D. Hallingdal
    Hallingdal is a major valley and traditional district in southeastern Norway, known for its river, ski resorts, and rich folk culture.
  • E. Trøndelag
    Trøndelag is a central region of Norway known for its historic city of Trondheim, coastal landscapes, and strong cultural traditions.
  • 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: Innlandet
Triple: [Kristiansund, composedOf, Innlandet]
Generated description
Innlandet is an island district of the Norwegian town of Kristiansund, known for its traditional wooden houses and coastal maritime character.
NED2 Entity disambiguation (via description) gpt-5-mini-2025-08-07 
Target entity: Innlandet
Target entity description: Innlandet is an island district of the Norwegian town of Kristiansund, known for its traditional wooden houses and coastal maritime character.
  • A. Innlandet
    Innlandet is a county in eastern Norway known for its inland landscapes, including mountains, forests, and important winter sports venues.
  • B. Hadeland
    Hadeland is a traditional rural district in southeastern Norway known for its agricultural landscape, historic churches, and the Hadeland Glassverk glassworks.
  • C. Numedal
    Numedal is a valley in southeastern Norway known for its traditional wooden architecture, medieval stave churches, and scenic river landscape.
  • D. Hallingdal
    Hallingdal is a major valley and traditional district in southeastern Norway, known for its river, ski resorts, and rich folk culture.
  • E. Trøndelag
    Trøndelag is a central region of Norway known for its historic city of Trondheim, coastal landscapes, and strong cultural traditions.
  • 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_69ad85d8042081908af94a04c410dec0 completed March 8, 2026, 2:21 p.m.
NER Named-entity recognition batch_69adc15bbbcc81908d6cf95f8e70c6ca completed March 8, 2026, 6:35 p.m.
NED1 Entity disambiguation (via context triple) batch_69b4030bc5f081908d56edc4ff550d77 completed March 13, 2026, 12:28 p.m.
NEDg Description generation batch_69b403c9f6788190be21ee4c849fba60 completed March 13, 2026, 12:32 p.m.
NED2 Entity disambiguation (via description) batch_69b408744dcc819081308b7182a40c88 completed March 13, 2026, 12:52 p.m.
Created at: March 8, 2026, 3:22 p.m.