Triple

T3987587
Position Surface form Disambiguated ID Type / Status
Subject White E86909 entity
Predicate hasVariant P455 FINISHED
Object Witte
Witte is a surname and term of Germanic origin that is related to the word "white" and is borne by various notable individuals and families.
 E68163 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: Witte | Statement: [White, hasVariant, Witte]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07 
Target entity: Witte
Context triple: [White, hasVariant, Witte]
  • A. Blanc
    Blanc is the surname of Mel Blanc, the legendary American voice actor best known for bringing to life many iconic Looney Tunes characters.
  • B. Blaauw
    Blaauw is a Dutch surname most notably associated with Gerrit Blaauw, a pioneering computer architect involved in the design of early IBM systems.
  • C. Rood-witten
    Rood-witten is a popular nickname for PSV Eindhoven, referring to the club’s traditional red-and-white team colors.
  • D. 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.
  • E. Weiss
    Weiss is a common German-language surname borne by numerous notable individuals across fields such as entertainment, science, and politics.
  • 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: Witte
Triple: [White, hasVariant, Witte]
Generated description
Witte is a surname and term of Germanic origin that is related to the word "white" and is borne by various notable individuals and families.
NED2 Entity disambiguation (via description) gpt-5-mini-2025-08-07 
Target entity: Witte
Target entity description: Witte is a surname and term of Germanic origin that is related to the word "white" and is borne by various notable individuals and families.
  • A. Blanc
    Blanc is the surname of Mel Blanc, the legendary American voice actor best known for bringing to life many iconic Looney Tunes characters.
  • B. Blaauw
    Blaauw is a Dutch surname most notably associated with Gerrit Blaauw, a pioneering computer architect involved in the design of early IBM systems.
  • C. Rood-witten
    Rood-witten is a popular nickname for PSV Eindhoven, referring to the club’s traditional red-and-white team colors.
  • D. 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.
  • E. Weiss chosen
    Weiss is a common German-language surname borne by numerous notable individuals across fields such as entertainment, science, and politics.
  • F. None of above.

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_69aed93fd9d4819085d3b2137d2346cb completed March 9, 2026, 2:29 p.m.
NER Named-entity recognition batch_69aef9ff54708190be56f48569ce97a4 completed March 9, 2026, 4:49 p.m.
NED1 Entity disambiguation (via context triple) batch_69b5402f72e8819097ce951aac465dc8 completed March 14, 2026, 11:02 a.m.
NEDg Description generation batch_69b54111e5188190ab8ec23124c22981 completed March 14, 2026, 11:05 a.m.
NED2 Entity disambiguation (via description) batch_69b54195261c8190a155b3c0469b0a35 completed March 14, 2026, 11:08 a.m.
Created at: March 9, 2026, 3:33 p.m.