Triple

T11289638
Position Surface form Disambiguated ID Type / Status
Subject Ryan Wittman E267290 entity
Predicate familyName P18 FINISHED
Object Wittman
Wittman is a surname of German origin borne by various notable individuals across fields such as sports, politics, and the arts.
 E915554 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: Wittman | Statement: [Ryan Wittman, familyName, Wittman]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07 
Target entity: Wittman
Context triple: [Ryan Wittman, familyName, Wittman]
  • A. Wickett
    Wickett is a small town located in Ward County in the western part of Texas, United States.
  • B. Tilghman
    Tilghman is a masculine given name of English origin that has been borne by various notable American figures, including politicians and military officers.
  • C. Zakheim
    Zakheim is a surname most notably associated with Bernard Zakheim, a Polish-born American muralist known for his New Deal–era public artworks in California.
  • D. Willetts
    Willetts is an English surname borne by various individuals, including figures in politics, academia, and sports.
  • E. Wittenborn
    Wittenborn was a notable mid-20th-century art and design book publisher known for producing influential works in modern art, architecture, and design.
  • 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: Wittman
Triple: [Ryan Wittman, familyName, Wittman]
Generated description
Wittman is a surname of German origin borne by various notable individuals across fields such as sports, politics, and the arts.
NED2 Entity disambiguation (via description) gpt-5-mini-2025-08-07 
Target entity: Wittman
Target entity description: Wittman is a surname of German origin borne by various notable individuals across fields such as sports, politics, and the arts.
  • A. Wickett
    Wickett is a small town located in Ward County in the western part of Texas, United States.
  • B. Tilghman
    Tilghman is a masculine given name of English origin that has been borne by various notable American figures, including politicians and military officers.
  • C. Zakheim
    Zakheim is a surname most notably associated with Bernard Zakheim, a Polish-born American muralist known for his New Deal–era public artworks in California.
  • D. Willetts
    Willetts is an English surname borne by various individuals, including figures in politics, academia, and sports.
  • E. Wittenborn
    Wittenborn was a notable mid-20th-century art and design book publisher known for producing influential works in modern art, architecture, and design.
  • 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_69d6aac993a08190a6f36445ebaf9a43 completed April 8, 2026, 7:21 p.m.
NER Named-entity recognition batch_69d7e98875a08190b8509fe55e49d52d completed April 9, 2026, 6:01 p.m.
NED1 Entity disambiguation (via context triple) batch_69e4f49badc88190a3195e919900f0c3 completed April 19, 2026, 3:28 p.m.
NEDg Description generation batch_69e4f95cbc7c819082e3d7c3c3266708 completed April 19, 2026, 3:48 p.m.
NED2 Entity disambiguation (via description) batch_69e4ff6b7d248190b4dd885280e09a8e completed April 19, 2026, 4:14 p.m.
Created at: April 8, 2026, 9:32 p.m.