Triple

T3910832
Position Surface form Disambiguated ID Type / Status
Subject Radboud University Nijmegen E87316 entity
Predicate abbreviation P43 FINISHED
Object RU
RU is the common abbreviation for Radboud University Nijmegen, a major research university located in Nijmegen, the Netherlands.
E398372 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: RU | Statement: [Radboud University Nijmegen, abbreviation, RU]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: RU
Context triple: [Radboud University Nijmegen, abbreviation, RU]
  • A. RU
    RU is the common abbreviation for Rutgers University, a major public research institution in New Jersey.
  • B. RU
    RU is the two-letter ISO 3166 country code for the Russian Federation.
  • C. RUS
    RUS is the acronym for the Rural Utilities Service, a U.S. government agency that provides funding and support for rural infrastructure such as electricity, water, and telecommunications.
  • D. RU-KOS
    RU-KOS is the ISO 3166-2 subdivision code assigned to Kostroma Oblast, a federal subject in central Russia.
  • E. Russin
    Russin is a small wine-producing municipality and village located in the canton of Geneva in southwestern Switzerland.
  • 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: RU
Triple: [Radboud University Nijmegen, abbreviation, RU]
Generated description
RU is the common abbreviation for Radboud University Nijmegen, a major research university located in Nijmegen, the Netherlands.
NED2 Entity disambiguation (via description) gpt-5-mini-2025-08-07
Target entity: RU
Target entity description: RU is the common abbreviation for Radboud University Nijmegen, a major research university located in Nijmegen, the Netherlands.
  • A. RU
    RU is the common abbreviation for Rutgers University, a major public research institution in New Jersey.
  • B. RU
    RU is the two-letter ISO 3166 country code for the Russian Federation.
  • C. RUS
    RUS is the acronym for the Rural Utilities Service, a U.S. government agency that provides funding and support for rural infrastructure such as electricity, water, and telecommunications.
  • D. RU-KOS
    RU-KOS is the ISO 3166-2 subdivision code assigned to Kostroma Oblast, a federal subject in central Russia.
  • E. Russin
    Russin is a small wine-producing municipality and village located in the canton of Geneva in southwestern Switzerland.
  • 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_69aed9424514819086e9c58adde6652d completed March 9, 2026, 2:29 p.m.
NER Named-entity recognition batch_69aeed3408f881908c3cffc5dbfe3950 completed March 9, 2026, 3:54 p.m.
NED1 Entity disambiguation (via context triple) batch_69b51cb454c48190bf47d080f6cc24f0 completed March 14, 2026, 8:30 a.m.
NEDg Description generation batch_69b5206dfd848190ae7aaa9997150934 completed March 14, 2026, 8:46 a.m.
NED2 Entity disambiguation (via description) batch_69b520ce6af481909b7824c2ec221331 completed March 14, 2026, 8:48 a.m.
Created at: March 9, 2026, 3:22 p.m.