Triple

T15243569
Position Surface form Disambiguated ID Type / Status
Subject Rana Municipality E364318 entity
Predicate contains P35 FINISHED
Object Dalsgrenda
Dalsgrenda is a small settlement located within Rana Municipality in Nordland county, Norway.
E1145498 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: Dalsgrenda | Statement: [Rana Municipality, contains, Dalsgrenda]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Dalsgrenda
Context triple: [Rana Municipality, contains, Dalsgrenda]
  • A. Thamerdal
    Thamerdal is a residential neighborhood within the Dutch town of Uithoorn in the province of North Holland.
  • B. Jättendal
    Jättendal is a small locality in northern Sweden, situated within Nordanstig Municipality in Gävleborg County.
  • C. Arvidsjaur
    Arvidsjaur is a small town in northern Sweden known for its military presence, winter testing facilities, and proximity to Arctic wilderness.
  • D. Skarpäng
    Skarpäng is a residential urban area within Täby Municipality in Stockholm County, Sweden.
  • E. Hedalen
    Hedalen is a rural village and valley area in Sør-Aurdal Municipality in Innlandet county, Norway, known for its historic stave church and scenic natural surroundings.
  • 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: Dalsgrenda
Triple: [Rana Municipality, contains, Dalsgrenda]
Generated description
Dalsgrenda is a small settlement located within Rana Municipality in Nordland county, Norway.
NED2 Entity disambiguation (via description) gpt-5-mini-2025-08-07
Target entity: Dalsgrenda
Target entity description: Dalsgrenda is a small settlement located within Rana Municipality in Nordland county, Norway.
  • A. Thamerdal
    Thamerdal is a residential neighborhood within the Dutch town of Uithoorn in the province of North Holland.
  • B. Jättendal
    Jättendal is a small locality in northern Sweden, situated within Nordanstig Municipality in Gävleborg County.
  • C. Arvidsjaur
    Arvidsjaur is a small town in northern Sweden known for its military presence, winter testing facilities, and proximity to Arctic wilderness.
  • D. Skarpäng
    Skarpäng is a residential urban area within Täby Municipality in Stockholm County, Sweden.
  • E. Hedalen
    Hedalen is a rural village and valley area in Sør-Aurdal Municipality in Innlandet county, Norway, known for its historic stave church and scenic natural surroundings.
  • 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_69d85a0dde7481908fc64d1e82d5d20d completed April 10, 2026, 2:01 a.m.
NER Named-entity recognition batch_69e007dcc33081908545ea1a1d2c19fe completed April 15, 2026, 9:49 p.m.
NED1 Entity disambiguation (via context triple) batch_69fedd461cf08190a506aac2f0cec83a completed May 9, 2026, 7:07 a.m.
NEDg Description generation batch_69fedf6ee3f081909553078cd3e9d243 completed May 9, 2026, 7:17 a.m.
NED2 Entity disambiguation (via description) batch_69fee0016a088190ad87268e035f677e completed May 9, 2026, 7:19 a.m.
Created at: April 10, 2026, 3:13 a.m.