Triple

T13294006
Position Surface form Disambiguated ID Type / Status
Subject Zwelinzima Vavi E316631 entity
Predicate placeOfBirth P1 FINISHED
Object Hanover
Hanover is a small town in South Africa, known as the birthplace of prominent trade unionist Zwelinzima Vavi.
 E1033079 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: Hanover | Statement: [Zwelinzima Vavi, placeOfBirth, Hanover]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07 
Target entity: Hanover
Context triple: [Zwelinzima Vavi, placeOfBirth, Hanover]
  • A. Hanover
    Hanover is a historic city in northern Germany that served as the capital of the former Kingdom of Hanover and the ancestral seat of the British House of Hanover.
  • B. Hanover
    Hanover is a small New Hampshire town best known as the home of Dartmouth College, an Ivy League institution.
  • C. Hanover
    Hanover is a small suburban town in Plymouth County, Massachusetts, known for its residential character and local businesses south of Boston.
  • D. Hanover
    Hanover is a surname most notably associated with Donna Hanover, an American journalist, actress, and former First Lady of New York City.
  • E. Hamburg
    Hamburg is Germany’s second-largest city and a major northern European port and cultural center on the River Elbe.
  • 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: Hanover
Triple: [Zwelinzima Vavi, placeOfBirth, Hanover]
Generated description
Hanover is a small town in South Africa, known as the birthplace of prominent trade unionist Zwelinzima Vavi.
NED2 Entity disambiguation (via description) gpt-5-mini-2025-08-07 
Target entity: Hanover
Target entity description: Hanover is a small town in South Africa, known as the birthplace of prominent trade unionist Zwelinzima Vavi.
  • A. Hanover
    Hanover is a historic city in northern Germany that served as the capital of the former Kingdom of Hanover and the ancestral seat of the British House of Hanover.
  • B. Hanover
    Hanover is a small New Hampshire town best known as the home of Dartmouth College, an Ivy League institution.
  • C. Hanover
    Hanover is a small suburban town in Plymouth County, Massachusetts, known for its residential character and local businesses south of Boston.
  • D. Hanover
    Hanover is a surname most notably associated with Donna Hanover, an American journalist, actress, and former First Lady of New York City.
  • E. Hamburg
    Hamburg is Germany’s second-largest city and a major northern European port and cultural center on the River Elbe.
  • 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_69d806b349908190a9a61dd9323bf153 completed April 9, 2026, 8:06 p.m.
NER Named-entity recognition batch_69d99078bcf0819083195fb556bcacb2 completed April 11, 2026, 12:06 a.m.
NED1 Entity disambiguation (via context triple) batch_69f716d8ee2081908428339216c43b47 completed May 3, 2026, 9:35 a.m.
NEDg Description generation batch_69f717b7b6dc8190ab323c1926dd9adb completed May 3, 2026, 9:39 a.m.
NED2 Entity disambiguation (via description) batch_69f7186b6218819096c67e9dd9af609f completed May 3, 2026, 9:42 a.m.
Created at: April 9, 2026, 9:28 p.m.