Triple

T4434686
Position Surface form Disambiguated ID Type / Status
Subject Jotunheimen E95619 entity
Predicate contains P35 FINISHED
Object Besseggen
Besseggen is a famous mountain ridge and hiking route in Norway known for its dramatic views between the lakes Gjende and Bessvatnet.
E446069 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: Besseggen | Statement: [Jotunheimen, contains, Besseggen]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Besseggen
Context triple: [Jotunheimen, contains, Besseggen]
  • A. Bettlach
    Bettlach is a Swiss municipality located in the canton of Solothurn.
  • B. Bönigen
    Bönigen is a Swiss village in the canton of Bern, known for its scenic location on the shore of Lake Brienz near Interlaken.
  • C. Oberegg
    Oberegg is a Swiss municipality in the canton of Appenzell Innerrhoden, known for its rural landscape and location in the Appenzell region.
  • D. Göschenen
    Göschenen is a Swiss mountain village and railway junction in the canton of Uri, known as a gateway to the Gotthard region.
  • E. Küsnacht
    Küsnacht is a picturesque Swiss municipality on the shores of Lake Zurich, known for its affluent residential character and scenic lakeside setting.
  • 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: Besseggen
Triple: [Jotunheimen, contains, Besseggen]
Generated description
Besseggen is a famous mountain ridge and hiking route in Norway known for its dramatic views between the lakes Gjende and Bessvatnet.
NED2 Entity disambiguation (via description) gpt-5-mini-2025-08-07
Target entity: Besseggen
Target entity description: Besseggen is a famous mountain ridge and hiking route in Norway known for its dramatic views between the lakes Gjende and Bessvatnet.
  • A. Bettlach
    Bettlach is a Swiss municipality located in the canton of Solothurn.
  • B. Bönigen
    Bönigen is a Swiss village in the canton of Bern, known for its scenic location on the shore of Lake Brienz near Interlaken.
  • C. Oberegg
    Oberegg is a Swiss municipality in the canton of Appenzell Innerrhoden, known for its rural landscape and location in the Appenzell region.
  • D. Göschenen
    Göschenen is a Swiss mountain village and railway junction in the canton of Uri, known as a gateway to the Gotthard region.
  • E. Küsnacht
    Küsnacht is a picturesque Swiss municipality on the shores of Lake Zurich, known for its affluent residential character and scenic lakeside setting.
  • 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_69bd56ada9508190ab5566490c527d3f completed March 20, 2026, 2:16 p.m.
NEDg Description generation batch_69bd62f8acb48190943f3c53ee985a5d completed March 20, 2026, 3:08 p.m.
NED2 Entity disambiguation (via description) batch_69bd636693d48190a94b2f6d5a6576a1 completed March 20, 2026, 3:10 p.m.
Created at: March 12, 2026, 11:31 p.m.