Triple

T10851989
Position Surface form Disambiguated ID Type / Status
Subject MCH Messecenter Herning E256167 entity
Predicate locatedOnStreet P959 FINISHED
Object Vardevej
Vardevej is a street in Herning, Denmark, known for providing access to the large exhibition and event complex MCH Messecenter Herning.
E888835 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: Vardevej | Statement: [MCH Messecenter Herning, locatedOnStreet, Vardevej]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Vardevej
Context triple: [MCH Messecenter Herning, locatedOnStreet, Vardevej]
  • A. Kerneveg
    Kerneveg is a dialect of the Breton language traditionally spoken in the Cornouaille (Kernev) region of western Brittany.
  • B. Bergambacht
    Bergambacht is a village in the Dutch province of South Holland, known as the birthplace of former Prime Minister Wim Kok.
  • C. Gammel Kongevej
    Gammel Kongevej is a major historic shopping and thoroughfare street in the Frederiksberg district of Copenhagen, known for its boutiques, cafés, and urban atmosphere.
  • D. Svenskens vei
    Svenskens vei is a street located in the Vålerenga neighborhood of Oslo, Norway.
  • E. Veavågen
    Veavågen is a coastal village in Karmøy municipality in Rogaland county, Norway, known for its fishing industry and maritime character.
  • 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: Vardevej
Triple: [MCH Messecenter Herning, locatedOnStreet, Vardevej]
Generated description
Vardevej is a street in Herning, Denmark, known for providing access to the large exhibition and event complex MCH Messecenter Herning.
NED2 Entity disambiguation (via description) gpt-5-mini-2025-08-07
Target entity: Vardevej
Target entity description: Vardevej is a street in Herning, Denmark, known for providing access to the large exhibition and event complex MCH Messecenter Herning.
  • A. Kerneveg
    Kerneveg is a dialect of the Breton language traditionally spoken in the Cornouaille (Kernev) region of western Brittany.
  • B. Bergambacht
    Bergambacht is a village in the Dutch province of South Holland, known as the birthplace of former Prime Minister Wim Kok.
  • C. Gammel Kongevej
    Gammel Kongevej is a major historic shopping and thoroughfare street in the Frederiksberg district of Copenhagen, known for its boutiques, cafés, and urban atmosphere.
  • D. Svenskens vei
    Svenskens vei is a street located in the Vålerenga neighborhood of Oslo, Norway.
  • E. Veavågen
    Veavågen is a coastal village in Karmøy municipality in Rogaland county, Norway, known for its fishing industry and maritime character.
  • 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_69d6aa83d1448190a66d93c32394d21f completed April 8, 2026, 7:20 p.m.
NER Named-entity recognition batch_69d75117b76c8190b0fb216b1428c3c7 completed April 9, 2026, 7:11 a.m.
NED1 Entity disambiguation (via context triple) batch_69deb17d978c8190883b4a56e88859de completed April 14, 2026, 9:28 p.m.
NEDg Description generation batch_69deb515ab608190981689bcad4b7530 completed April 14, 2026, 9:43 p.m.
NED2 Entity disambiguation (via description) batch_69deb602fa908190bffdd291932da3f1 completed April 14, 2026, 9:47 p.m.
Created at: April 8, 2026, 9:20 p.m.