Triple

T983414
Position Surface form Disambiguated ID Type / Status
Subject Baker E21223 entity
Predicate hasVariant P455 FINISHED
Object Becker
Becker is a surname of German origin, commonly associated with individuals in German-speaking countries and their descendants worldwide.
 E115890 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: Becker | Statement: [Baker, hasVariant, Becker]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07 
Target entity: Becker
Context triple: [Baker, hasVariant, Becker]
  • A. Pinsker
    Pinsker is a Jewish surname most notably associated with Leo Pinsker, a 19th-century physician and early Zionist activist.
  • B. Beranek
    Beranek is a surname most notably associated with Leo Beranek, an American acoustics expert and co-founder of the engineering firm Bolt, Beranek and Newman (BBN).
  • C. Blaustein
    Blaustein is a municipality in the Alb-Donau district of Baden-Württemberg in southern Germany, situated near the city of Ulm.
  • D. Tucker
    Tucker is a surname most notably associated with Albert W. Tucker, a Canadian-American mathematician and game theorist known for his contributions to topology and the formalization of the prisoner's dilemma.
  • E. Blatch
    Blatch is the surname of Nora Stanton Blatch, an early 20th-century American civil engineer, suffragist, and women's rights activist.
  • 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: Becker
Triple: [Baker, hasVariant, Becker]
Generated description
Becker is a surname of German origin, commonly associated with individuals in German-speaking countries and their descendants worldwide.
NED2 Entity disambiguation (via description) gpt-5-mini-2025-08-07 
Target entity: Becker
Target entity description: Becker is a surname of German origin, commonly associated with individuals in German-speaking countries and their descendants worldwide.
  • A. Pinsker
    Pinsker is a Jewish surname most notably associated with Leo Pinsker, a 19th-century physician and early Zionist activist.
  • B. Beranek
    Beranek is a surname most notably associated with Leo Beranek, an American acoustics expert and co-founder of the engineering firm Bolt, Beranek and Newman (BBN).
  • C. Blaustein
    Blaustein is a municipality in the Alb-Donau district of Baden-Württemberg in southern Germany, situated near the city of Ulm.
  • D. Tucker
    Tucker is a surname most notably associated with Albert W. Tucker, a Canadian-American mathematician and game theorist known for his contributions to topology and the formalization of the prisoner's dilemma.
  • E. Blatch
    Blatch is the surname of Nora Stanton Blatch, an early 20th-century American civil engineer, suffragist, and women's rights activist.
  • 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_69a493c383dc8190a03257f22d4b4183 completed March 1, 2026, 7:30 p.m.
NER Named-entity recognition batch_69a4b493f5dc819090d239c2f7e083de completed March 1, 2026, 9:50 p.m.
NED1 Entity disambiguation (via context triple) batch_69ac1ce3c6fc81909fbbf04eef1b997e completed March 7, 2026, 12:41 p.m.
NEDg Description generation batch_69ac1d45b8cc8190b8b678b697d3f7f1 completed March 7, 2026, 12:42 p.m.
NED2 Entity disambiguation (via description) batch_69ac1e2e200881909e9b503655d6f8ab completed March 7, 2026, 12:46 p.m.
Created at: March 1, 2026, 7:41 p.m.