Triple

T21293212
Position Surface form Disambiguated ID Type / Status
Subject Aarburg E524848 entity
Predicate neighboringMunicipality P17964 FINISHED
Object Riken
Riken is a small municipality in the canton of Aargau in northern Switzerland.
E1476686 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: Riken | Statement: [Aarburg, neighboringMunicipality, Riken]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Riken
Context triple: [Aarburg, neighboringMunicipality, Riken]
  • A. Riken
    Riken is a Japanese automotive parts manufacturer best known for producing piston rings and related engine components for global vehicle makers.
  • B. RIKEN
    RIKEN is Japan’s largest comprehensive research institution, renowned for its cutting-edge work in physics, chemistry, biology, medical science, and engineering.
  • C. National Institute of Genetics
    The National Institute of Genetics is a leading Japanese research institute specializing in genetics and genomics, known for pioneering work in evolutionary biology and molecular genetics.
  • D. Ibuka Laboratory
    Ibuka Laboratory was an electronics research workshop in postwar Tokyo that became the foundation for what would later grow into Sony.
  • E. Koto Laboratory
    Koto Laboratory is a Japanese game development studio established by legendary Nintendo designer Gunpei Yokoi after his departure from the company.
  • 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: Riken
Triple: [Aarburg, neighboringMunicipality, Riken]
Generated description
Riken is a small municipality in the canton of Aargau in northern Switzerland.
NED2 Entity disambiguation (via description) gpt-5-mini-2025-08-07
Target entity: Riken
Target entity description: Riken is a small municipality in the canton of Aargau in northern Switzerland.
  • A. Riken
    Riken is a Japanese automotive parts manufacturer best known for producing piston rings and related engine components for global vehicle makers.
  • B. RIKEN
    RIKEN is Japan’s largest comprehensive research institution, renowned for its cutting-edge work in physics, chemistry, biology, medical science, and engineering.
  • C. National Institute of Genetics
    The National Institute of Genetics is a leading Japanese research institute specializing in genetics and genomics, known for pioneering work in evolutionary biology and molecular genetics.
  • D. Ibuka Laboratory
    Ibuka Laboratory was an electronics research workshop in postwar Tokyo that became the foundation for what would later grow into Sony.
  • E. Koto Laboratory
    Koto Laboratory is a Japanese game development studio established by legendary Nintendo designer Gunpei Yokoi after his departure from the company.
  • 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_69e0b517e6748190850d6f6ddf323d69 completed April 16, 2026, 10:08 a.m.
NER Named-entity recognition batch_69e73856ba988190a8359efecea362cc completed April 21, 2026, 8:41 a.m.
NED1 Entity disambiguation (via context triple) batch_6a099810106c8190a2ee5789bd0380c6 completed May 17, 2026, 10:27 a.m.
NEDg Description generation batch_6a0998d6b37881908a1b09afc1f67746 completed May 17, 2026, 10:30 a.m.
NED2 Entity disambiguation (via description) batch_6a0999884e0481909b7ea54cd7ef87b5 completed May 17, 2026, 10:33 a.m.
Created at: April 16, 2026, 4:04 p.m.