Triple

T17370092
Position Surface form Disambiguated ID Type / Status
Subject Telemark Canal E422287 entity
Predicate connectsTo P845 FINISHED
Object Dalen — NE ONDG

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: Dalen | Statement: [Telemark Canal, connectsTo, Dalen]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07 
Target entity: Dalen
Context triple: [Telemark Canal, connectsTo, Dalen]
  • A. Lodalen
    Lodalen is a small valley and residential-industrial area in Oslo, Norway, situated near the inner-city districts and railway facilities.
  • B. Dalén
    Dalén is a Swedish surname most notably associated with Nobel Prize–winning engineer and inventor Nils Gustaf Dalén.
  • C. Eidskog
    Eidskog is a rural municipality in Innlandet county, Norway, known for its forests, lakes, and location along the Swedish border.
  • D. Flesberg
    Flesberg is a rural municipality in southeastern Norway known for its forests, traditional wooden architecture, and location in the Numedal valley.
  • E. Djursholm
    Djursholm is an affluent suburban district of Stockholm, Sweden, known for its villas, garden-city planning, and status as one of the country’s wealthiest residential areas.
  • 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: Dalen
Triple: [Telemark Canal, connectsTo, Dalen]
NED2 Entity disambiguation (via description) gpt-5-mini-2025-08-07 
Target entity: Dalen
Target entity description: Dalen is a small village in Tokke Municipality, Norway, known as the western terminus of the historic Telemark Canal and a gateway to the surrounding mountainous landscape.
  • A. Lodalen
    Lodalen is a small valley and residential-industrial area in Oslo, Norway, situated near the inner-city districts and railway facilities.
  • B. Dalén
    Dalén is a Swedish surname most notably associated with Nobel Prize–winning engineer and inventor Nils Gustaf Dalén.
  • C. Eidskog
    Eidskog is a rural municipality in Innlandet county, Norway, known for its forests, lakes, and location along the Swedish border.
  • D. Flesberg
    Flesberg is a rural municipality in southeastern Norway known for its forests, traditional wooden architecture, and location in the Numedal valley.
  • E. Djursholm
    Djursholm is an affluent suburban district of Stockholm, Sweden, known for its villas, garden-city planning, and status as one of the country’s wealthiest residential areas.
  • F. None of above. chosen

Provenance (4 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_69d889d6535c81908be333c01deaec4e completed April 10, 2026, 5:25 a.m.
NER Named-entity recognition batch_69e43a6842388190940235198fa50041 completed April 19, 2026, 2:14 a.m.
NED1 Entity disambiguation (via context triple) batch_6a019566da6c819083b59e0911d02bd5 completed May 11, 2026, 8:37 a.m.
NEDg Description generation batch_6a01962ae4848190b2aad8e19bf6522f in_progress May 11, 2026, 8:41 a.m.
Created at: April 10, 2026, 5:44 a.m.