Triple

T17611698
Position Surface form Disambiguated ID Type / Status
Subject Christianization of Frisia E428978 entity
Predicate hasMajorMissionary P72272 FINISHED
Object Suitbert
Suitbert was a 7th-century Anglo-Saxon missionary and bishop known for his role in spreading Christianity among the Frisians and other Germanic peoples.
 E1277661 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: Suitbert | Statement: [Christianization of Frisia, hasMajorMissionary, Suitbert]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07 
Target entity: Suitbert
Context triple: [Christianization of Frisia, hasMajorMissionary, Suitbert]
  • A. The Vern
    The Vern is the informal name for George Washington University's Mount Vernon Campus in Washington, D.C.
  • B. Knightwick
    Knightwick is a small rural village in Worcestershire, England, situated near the River Teme and the Malvern Hills.
  • C. Bigloo
    Bigloo is a high-performance Scheme implementation and compiler designed to generate efficient C, Java, and .NET code for practical application development.
  • D. Mr. Nice
    Mr. Nice is a 2010 biographical crime film in which Rhys Ifans portrays real-life Welsh drug smuggler Howard Marks.
  • E. Bert
    Bert is a masculine given name, often used as a short form of names like Albert, Herbert, or Bertram.
  • 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: Suitbert
Triple: [Christianization of Frisia, hasMajorMissionary, Suitbert]
Generated description
Suitbert was a 7th-century Anglo-Saxon missionary and bishop known for his role in spreading Christianity among the Frisians and other Germanic peoples.
NED2 Entity disambiguation (via description) gpt-5-mini-2025-08-07 
Target entity: Suitbert
Target entity description: Suitbert was a 7th-century Anglo-Saxon missionary and bishop known for his role in spreading Christianity among the Frisians and other Germanic peoples.
  • A. The Vern
    The Vern is the informal name for George Washington University's Mount Vernon Campus in Washington, D.C.
  • B. Knightwick
    Knightwick is a small rural village in Worcestershire, England, situated near the River Teme and the Malvern Hills.
  • C. Bigloo
    Bigloo is a high-performance Scheme implementation and compiler designed to generate efficient C, Java, and .NET code for practical application development.
  • D. Mr. Nice
    Mr. Nice is a 2010 biographical crime film in which Rhys Ifans portrays real-life Welsh drug smuggler Howard Marks.
  • E. Bert
    Bert is a serious, detail-oriented Muppet from Sesame Street, best known for his love of pigeons, paper clips, and his comedic odd-couple friendship with Ernie.
  • 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_69d889e1c6148190ba76241e74688f8b completed April 10, 2026, 5:25 a.m.
NER Named-entity recognition batch_69e46d2dfa688190a0b9b396bb6133cc completed April 19, 2026, 5:50 a.m.
NED1 Entity disambiguation (via context triple) batch_6a01e8241cb481909ebb91e24c6eaf63 completed May 11, 2026, 2:31 p.m.
NEDg Description generation batch_6a01ee1a291c81909fa432ccc787028f completed May 11, 2026, 2:56 p.m.
NED2 Entity disambiguation (via description) batch_6a01eec7e00c81908d88be9f88e924c8 completed May 11, 2026, 2:59 p.m.
Created at: April 10, 2026, 5:51 a.m.