Triple

T5965517
Position Surface form Disambiguated ID Type / Status
Subject Inderøy E132741 entity
Predicate previousCounty P65436 FINISHED
Object Nord-Trøndelag
Nord-Trøndelag was a former county in central Norway known for its rural landscapes, coastal areas, and agricultural communities before it merged into Trøndelag county in 2018.
E17971 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: Nord-Trøndelag | Statement: [Inderøy, previousCounty, Nord-Trøndelag]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Nord-Trøndelag
Context triple: [Inderøy, previousCounty, Nord-Trøndelag]
  • A. Trøndelag
    Trøndelag is a central region of Norway known for its historic city of Trondheim, coastal landscapes, and strong cultural traditions.
  • B. Møre og Romsdal
    Møre og Romsdal is a coastal county in western Norway known for its dramatic fjords, islands, and mountainous landscapes.
  • C. Sogn og Fjordane
    Sogn og Fjordane was a former county in western Norway known for its dramatic fjords, mountains, and coastal landscapes.
  • D. Hedmark
    Hedmark is a former county in eastern Norway known for its vast forests, agriculture, and inland landscapes along the Swedish border.
  • E. Hedmarken
    Hedmarken is a traditional district in Innlandet county in eastern Norway, known for its agricultural landscapes and its central town, Hamar.
  • 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: Nord-Trøndelag
Triple: [Inderøy, previousCounty, Nord-Trøndelag]
Generated description
Nord-Trøndelag was a former county in central Norway known for its rural landscapes, coastal areas, and agricultural communities before it merged into Trøndelag county in 2018.
NED2 Entity disambiguation (via description) gpt-5-mini-2025-08-07
Target entity: Nord-Trøndelag
Target entity description: Nord-Trøndelag was a former county in central Norway known for its rural landscapes, coastal areas, and agricultural communities before it merged into Trøndelag county in 2018.
  • A. Trøndelag chosen
    Trøndelag is a central region of Norway known for its historic city of Trondheim, coastal landscapes, and strong cultural traditions.
  • B. Møre og Romsdal
    Møre og Romsdal is a coastal county in western Norway known for its dramatic fjords, islands, and mountainous landscapes.
  • C. Sogn og Fjordane
    Sogn og Fjordane was a former county in western Norway known for its dramatic fjords, mountains, and coastal landscapes.
  • D. Hedmark
    Hedmark is a former county in eastern Norway known for its vast forests, agriculture, and inland landscapes along the Swedish border.
  • E. Hedmarken
    Hedmarken is a traditional district in Innlandet county in eastern Norway, known for its agricultural landscapes and its central town, Hamar.
  • F. None of above.

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_69c0086c2364819091e9fe2f58fa2517 completed March 22, 2026, 3:19 p.m.
NER Named-entity recognition batch_69c03a3ca1dc819098cde8ae5ec1d845 completed March 22, 2026, 6:51 p.m.
NED1 Entity disambiguation (via context triple) batch_69c7005bdc8881908e116147fe9b0abf completed March 27, 2026, 10:10 p.m.
NEDg Description generation batch_69c701fa048c819091585d2bd4afe06a completed March 27, 2026, 10:17 p.m.
NED2 Entity disambiguation (via description) batch_69c7028710788190b054c7cfd28a6812 completed March 27, 2026, 10:19 p.m.
Created at: March 22, 2026, 4:03 p.m.