Triple

T14560965
Position Surface form Disambiguated ID Type / Status
Subject Inderhavnen E341662 entity
Predicate adjacentTo P224 FINISHED
Object Holmen
Holmen is a historic waterfront district in Copenhagen, Denmark, known for its former naval base, repurposed industrial buildings, and vibrant cultural and residential developments.
E1106656 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: Holmen | Statement: [Inderhavnen, adjacentTo, Holmen]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Holmen
Context triple: [Inderhavnen, adjacentTo, Holmen]
  • A. Holmen
    Holmen is a residential neighborhood in Oslo, Norway, known for its green surroundings and location within the borough of Vestre Aker.
  • B. Hafslund
    Hafslund is a major Norwegian energy and utility company known for its role in electricity production, distribution, and related services.
  • C. Hestnes
    Hestnes is a small settlement located within the municipality of Eigersund in Rogaland county, southwestern Norway.
  • D. Haslum
    Haslum is a suburban area in Bærum, Norway, known for its residential neighborhoods and proximity to Oslo.
  • E. Holm
    Holm is a small rural settlement in the Orkney Islands of Scotland, known for its coastal landscape and historic island community.
  • 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: Holmen
Triple: [Inderhavnen, adjacentTo, Holmen]
Generated description
Holmen is a historic waterfront district in Copenhagen, Denmark, known for its former naval base, repurposed industrial buildings, and vibrant cultural and residential developments.
NED2 Entity disambiguation (via description) gpt-5-mini-2025-08-07
Target entity: Holmen
Target entity description: Holmen is a historic waterfront district in Copenhagen, Denmark, known for its former naval base, repurposed industrial buildings, and vibrant cultural and residential developments.
  • A. Holmen
    Holmen is a residential neighborhood in Oslo, Norway, known for its green surroundings and location within the borough of Vestre Aker.
  • B. Hafslund
    Hafslund is a major Norwegian energy and utility company known for its role in electricity production, distribution, and related services.
  • C. Hestnes
    Hestnes is a small settlement located within the municipality of Eigersund in Rogaland county, southwestern Norway.
  • D. Haslum
    Haslum is a suburban area in Bærum, Norway, known for its residential neighborhoods and proximity to Oslo.
  • E. Holm
    Holm is a small rural settlement in the Orkney Islands of Scotland, known for its coastal landscape and historic island community.
  • 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_69d822dcc6248190bed689984bceb0e2 completed April 9, 2026, 10:06 p.m.
NER Named-entity recognition batch_69deb389d0f48190a1d9d69456d1cbe1 completed April 14, 2026, 9:37 p.m.
NED1 Entity disambiguation (via context triple) batch_69fd8ac294748190a4bfeed8c5fd9e94 completed May 8, 2026, 7:03 a.m.
NEDg Description generation batch_69fd8c3678048190a23b509e963c1ade completed May 8, 2026, 7:09 a.m.
NED2 Entity disambiguation (via description) batch_69fd8d609684819090a9c3f2304f4a6a completed May 8, 2026, 7:14 a.m.
Created at: April 10, 2026, 1:23 a.m.