Triple

T6418522
Position Surface form Disambiguated ID Type / Status
Subject Charles Robberts Swart E127887 entity
Predicate familyName P18 FINISHED
Object Swart
Swart is a surname of Afrikaans and Dutch origin, notably borne by Charles Robberts Swart, the first State President of South Africa.
 E593260 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: Swart | Statement: [Charles Robberts Swart, familyName, Swart]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07 
Target entity: Swart
Context triple: [Charles Robberts Swart, familyName, Swart]
  • A. Schwaz
    Schwaz is a historic silver-mining town in the Austrian state of Tyrol, known for its medieval center and alpine setting.
  • B. Zwartsluis
    Zwartsluis is a small Dutch town in the province of Overijssel, known for its waterways, historic harbor, and role as a regional boating and water sports hub.
  • C. Schwarz
    Schwarz is a theoretical physicist best known as one of the pioneers of string theory and for his work on anomaly cancellation.
  • D. Blaauw
    Blaauw is a Dutch surname most notably associated with Gerrit Blaauw, a pioneering computer architect involved in the design of early IBM systems.
  • E. Blau
    The Blau is a small river in the German state of Baden-Württemberg that flows through the city of Blaustein before joining the Danube.
  • 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: Swart
Triple: [Charles Robberts Swart, familyName, Swart]
Generated description
Swart is a surname of Afrikaans and Dutch origin, notably borne by Charles Robberts Swart, the first State President of South Africa.
NED2 Entity disambiguation (via description) gpt-5-mini-2025-08-07 
Target entity: Swart
Target entity description: Swart is a surname of Afrikaans and Dutch origin, notably borne by Charles Robberts Swart, the first State President of South Africa.
  • A. Schwaz
    Schwaz is a historic silver-mining town in the Austrian state of Tyrol, known for its medieval center and alpine setting.
  • B. Zwartsluis
    Zwartsluis is a small Dutch town in the province of Overijssel, known for its waterways, historic harbor, and role as a regional boating and water sports hub.
  • C. Schwarz
    Schwarz is a theoretical physicist best known as one of the pioneers of string theory and for his work on anomaly cancellation.
  • D. Blaauw
    Blaauw is a Dutch surname most notably associated with Gerrit Blaauw, a pioneering computer architect involved in the design of early IBM systems.
  • E. Blau
    The Blau is a small river in the German state of Baden-Württemberg that flows through the city of Blaustein before joining the Danube.
  • 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_69c0083815208190a9b299b8e0640218 completed March 22, 2026, 3:18 p.m.
NER Named-entity recognition batch_69c068eb6c988190b54de6182d0f490d completed March 22, 2026, 10:10 p.m.
NED1 Entity disambiguation (via context triple) batch_69c640d2ab64819089e91525da60392b completed March 27, 2026, 8:33 a.m.
NEDg Description generation batch_69c644ec2ca48190997a118f8751cba5 completed March 27, 2026, 8:50 a.m.
NED2 Entity disambiguation (via description) batch_69c6455961b881908f5804d9c0e86573 completed March 27, 2026, 8:52 a.m.
Created at: March 22, 2026, 4:42 p.m.