Triple

T1695015
Position Surface form Disambiguated ID Type / Status
Subject Krefeld E36636 entity
Predicate hasCityDistrict P2709 FINISHED
Object Linn
Linn is a historic district of the German city of Krefeld, known for its medieval castle and well-preserved old town.
 E191563 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: Linn | Statement: [Krefeld, hasCityDistrict, Linn]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07 
Target entity: Linn
Context triple: [Krefeld, hasCityDistrict, Linn]
  • A. Lyness
    Lyness is a small coastal village and former naval base on the island of Hoy in Orkney, Scotland.
  • B. Lenno
    Lenno is a picturesque village on the western shore of Lake Como in northern Italy, known for its scenic waterfront and historic villas.
  • C. Sollentuna
    Sollentuna is a suburban town in Stockholm County, Sweden, known as part of the Stockholm urban area and a residential and commercial hub just north of the capital.
  • D. Lindeberg
    Lindeberg is a surname most notably associated with the Finnish mathematician Jarl Waldemar Lindeberg, known for his contributions to probability theory and the central limit theorem.
  • E. Nólsoy
    Nólsoy is a small, sparsely populated island in the Faroe Islands known for its traditional village, rich birdlife, and proximity to the capital, Tórshavn.
  • 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: Linn
Triple: [Krefeld, hasCityDistrict, Linn]
Generated description
Linn is a historic district of the German city of Krefeld, known for its medieval castle and well-preserved old town.
NED2 Entity disambiguation (via description) gpt-5-mini-2025-08-07 
Target entity: Linn
Target entity description: Linn is a historic district of the German city of Krefeld, known for its medieval castle and well-preserved old town.
  • A. Lyness
    Lyness is a small coastal village and former naval base on the island of Hoy in Orkney, Scotland.
  • B. Lenno
    Lenno is a picturesque village on the western shore of Lake Como in northern Italy, known for its scenic waterfront and historic villas.
  • C. Sollentuna
    Sollentuna is a suburban town in Stockholm County, Sweden, known as part of the Stockholm urban area and a residential and commercial hub just north of the capital.
  • D. Lindeberg
    Lindeberg is a surname most notably associated with the Finnish mathematician Jarl Waldemar Lindeberg, known for his contributions to probability theory and the central limit theorem.
  • E. Nólsoy
    Nólsoy is a small, sparsely populated island in the Faroe Islands known for its traditional village, rich birdlife, and proximity to the capital, Tórshavn.
  • 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_69a886163dec8190859c514232a37a05 completed March 4, 2026, 7:20 p.m.
NER Named-entity recognition batch_69aa62b3b8908190afc3f9e4a384684f completed March 6, 2026, 5:14 a.m.
NED1 Entity disambiguation (via context triple) batch_69ad7998e1108190aa7430cd4ef887d9 completed March 8, 2026, 1:28 p.m.
NEDg Description generation batch_69ad7a224d248190b0d1a7f70b76c164 completed March 8, 2026, 1:31 p.m.
NED2 Entity disambiguation (via description) batch_69ad7b4b4a208190966fa07a6f0d626e completed March 8, 2026, 1:36 p.m.
Created at: March 4, 2026, 7:30 p.m.