Triple

T7488746
Position Surface form Disambiguated ID Type / Status
Subject Limfjord E176948 entity
Predicate hasIsland P970 FINISHED
Object Venø
Venø is a small Danish island in the Limfjord known for its scenic landscapes, birdlife, and traditional coastal village atmosphere.
 E669131 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: Venø | Statement: [Limfjord, hasIsland, Venø]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07 
Target entity: Venø
Context triple: [Limfjord, hasIsland, Venø]
  • A. Odense River
    The Odense River is a waterway on the Danish island of Funen that flows through the city of Odense before emptying into Odense Fjord.
  • B. Kolding River
    Kolding River is a watercourse in southern Denmark that flows through the city of Kolding before emptying into Kolding Fjord.
  • C. Vesdre
    The Vesdre is a river in eastern Belgium that flows through the Ardennes and Liège region before joining the Meuse.
  • D. Limfjord
    Limfjord is a shallow sound and strait in northern Denmark that separates the northern tip of the Jutland Peninsula from the rest of the mainland and connects the North Sea with the Kattegat.
  • E. Vasagatan
    Vasagatan is a major central street in Stockholm, Sweden, known for its busy traffic, shops, and proximity to Stockholm Central Station.
  • 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: Venø
Triple: [Limfjord, hasIsland, Venø]
Generated description
Venø is a small Danish island in the Limfjord known for its scenic landscapes, birdlife, and traditional coastal village atmosphere.
NED2 Entity disambiguation (via description) gpt-5-mini-2025-08-07 
Target entity: Venø
Target entity description: Venø is a small Danish island in the Limfjord known for its scenic landscapes, birdlife, and traditional coastal village atmosphere.
  • A. Odense River
    The Odense River is a waterway on the Danish island of Funen that flows through the city of Odense before emptying into Odense Fjord.
  • B. Kolding River
    Kolding River is a watercourse in southern Denmark that flows through the city of Kolding before emptying into Kolding Fjord.
  • C. Vesdre
    The Vesdre is a river in eastern Belgium that flows through the Ardennes and Liège region before joining the Meuse.
  • D. Limfjord
    Limfjord is a shallow sound and strait in northern Denmark that separates the northern tip of the Jutland Peninsula from the rest of the mainland and connects the North Sea with the Kattegat.
  • E. Vasagatan
    Vasagatan is a major central street in Stockholm, Sweden, known for its busy traffic, shops, and proximity to Stockholm Central Station.
  • 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_69c69f24ac508190bb98fe927c0bd065 completed March 27, 2026, 3:15 p.m.
NER Named-entity recognition batch_69c6f55abcd481909e42ca857fe46cd1 completed March 27, 2026, 9:23 p.m.
NED1 Entity disambiguation (via context triple) batch_69c83c71f5748190bdda4cf9b8dfc6ea completed March 28, 2026, 8:39 p.m.
NEDg Description generation batch_69c83e7b2ab08190a5ecb9b87af067a5 completed March 28, 2026, 8:47 p.m.
NED2 Entity disambiguation (via description) batch_69c842bad1e8819093bf61d9480dbd22 completed March 28, 2026, 9:06 p.m.
Created at: March 27, 2026, 3:43 p.m.