Triple

T4434677
Position Surface form Disambiguated ID Type / Status
Subject Buskerud E95618 entity
Predicate contains P35 FINISHED
Object Flesberg
Flesberg is a rural municipality in southeastern Norway known for its forests, traditional wooden architecture, and location in the Numedal valley.
E445703 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: Flesberg | Statement: [Buskerud, contains, Flesberg]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Flesberg
Context triple: [Buskerud, contains, Flesberg]
  • A. Fagernes
    Fagernes is a small town in central Norway that serves as a regional hub and gateway to the mountainous Valdres district.
  • B. Blakstad
    Blakstad is a village in Agder county, Norway, known as the main local hub for services and administration in the surrounding Froland area.
  • C. Hafslund
    Hafslund is a major Norwegian energy and utility company known for its role in electricity production, distribution, and related services.
  • D. Ullensvang
    Ullensvang is a scenic municipality in Vestland county, Norway, known for its fruit orchards, fjord landscapes, and location along the Hardangerfjord.
  • E. Mortensrud
    Mortensrud is a residential neighborhood in the Søndre Nordstrand borough of Oslo, Norway, known for its multicultural population and modern church, and served as the terminus of an Oslo Metro line.
  • 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: Flesberg
Triple: [Buskerud, contains, Flesberg]
Generated description
Flesberg is a rural municipality in southeastern Norway known for its forests, traditional wooden architecture, and location in the Numedal valley.
NED2 Entity disambiguation (via description) gpt-5-mini-2025-08-07
Target entity: Flesberg
Target entity description: Flesberg is a rural municipality in southeastern Norway known for its forests, traditional wooden architecture, and location in the Numedal valley.
  • A. Fagernes
    Fagernes is a small town in central Norway that serves as a regional hub and gateway to the mountainous Valdres district.
  • B. Blakstad
    Blakstad is a village in Agder county, Norway, known as the main local hub for services and administration in the surrounding Froland area.
  • C. Hafslund
    Hafslund is a major Norwegian energy and utility company known for its role in electricity production, distribution, and related services.
  • D. Ullensvang
    Ullensvang is a scenic municipality in Vestland county, Norway, known for its fruit orchards, fjord landscapes, and location along the Hardangerfjord.
  • E. Mortensrud
    Mortensrud is a residential neighborhood in the Søndre Nordstrand borough of Oslo, Norway, known for its multicultural population and modern church, and served as the terminus of an Oslo Metro line.
  • 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_69b3453ea2b48190a26f154b3b8fece5 completed March 12, 2026, 10:59 p.m.
NER Named-entity recognition batch_69b35588e99881908fea7b71a33e2bb6 completed March 13, 2026, 12:08 a.m.
NED1 Entity disambiguation (via context triple) batch_69bb80cd81d08190ad1d65091cecdfac completed March 19, 2026, 4:51 a.m.
NEDg Description generation batch_69bb839526c48190adeb2a8bccc82ff2 completed March 19, 2026, 5:03 a.m.
NED2 Entity disambiguation (via description) batch_69bb83ddb6ac8190bb5d48b27f2511b1 completed March 19, 2026, 5:04 a.m.
Created at: March 12, 2026, 11:31 p.m.