Triple

T19619154
Position Surface form Disambiguated ID Type / Status
Subject Raufoss E470951 entity
Predicate hasRiver P165 FINISHED
Object Hunnselva
Hunnselva is a river in Innlandet county, Norway, flowing through the town of Raufoss and contributing to the local industrial and natural landscape.
 E1432690 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: Hunnselva | Statement: [Raufoss, hasRiver, Hunnselva]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07 
Target entity: Hunnselva
Context triple: [Raufoss, hasRiver, Hunnselva]
  • A. Fykseelva
    Fykseelva is a river flowing through the municipality of Kvam in Vestland county, western Norway, known for its scenic valley and salmon fishing.
  • B. Verdalselva
    Verdalselva is a river in Trøndelag county, Norway, known for flowing through the Verdalen valley and supporting local agriculture, recreation, and salmon fishing.
  • C. Målselva
    Målselva is a major river in Troms, northern Norway, known for its salmon fishing and scenic valley landscapes.
  • D. Lærdalselvi
    Lærdalselvi is a renowned salmon river in western Norway, flowing through the Lærdal valley to the Sognefjord and known for both its fishing and scenic landscape.
  • E. Namsenelva
    Namsenelva is a major river in Trøndelag county, Norway, renowned as one of the country’s best salmon-fishing rivers.
  • 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: Hunnselva
Triple: [Raufoss, hasRiver, Hunnselva]
Generated description
Hunnselva is a river in Innlandet county, Norway, flowing through the town of Raufoss and contributing to the local industrial and natural landscape.
NED2 Entity disambiguation (via description) gpt-5-mini-2025-08-07 
Target entity: Hunnselva
Target entity description: Hunnselva is a river in Innlandet county, Norway, flowing through the town of Raufoss and contributing to the local industrial and natural landscape.
  • A. Fykseelva
    Fykseelva is a river flowing through the municipality of Kvam in Vestland county, western Norway, known for its scenic valley and salmon fishing.
  • B. Verdalselva
    Verdalselva is a river in Trøndelag county, Norway, known for flowing through the Verdalen valley and supporting local agriculture, recreation, and salmon fishing.
  • C. Målselva
    Målselva is a major river in Troms, northern Norway, known for its salmon fishing and scenic valley landscapes.
  • D. Lærdalselvi
    Lærdalselvi is a renowned salmon river in western Norway, flowing through the Lærdal valley to the Sognefjord and known for both its fishing and scenic landscape.
  • E. Namsenelva
    Namsenelva is a major river in Trøndelag county, Norway, renowned as one of the country’s best salmon-fishing rivers.
  • 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_69d8e510fa248190b7afb274a1d4cf73 completed April 10, 2026, 11:54 a.m.
NER Named-entity recognition batch_69e640e4570c81909fc4f9b871346337 completed April 20, 2026, 3:06 p.m.
NED1 Entity disambiguation (via context triple) batch_6a088af8db308190afb69c173d8f24ee completed May 16, 2026, 3:19 p.m.
NEDg Description generation batch_6a088c9b40788190b76ef5c582996d34 completed May 16, 2026, 3:26 p.m.
NED2 Entity disambiguation (via description) batch_6a088d186a38819085c8809560e94745 completed May 16, 2026, 3:28 p.m.
Created at: April 10, 2026, 1:43 p.m.