Triple

T1421638
Position Surface form Disambiguated ID Type / Status
Subject Grete Hermann E30237 entity
Predicate givenName P17 FINISHED
Object Grete
Grete is the given name of Grete Hermann, a German mathematician and philosopher known for her pioneering work in the foundations of quantum mechanics and computer algebra.
E163883 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: Grete | Statement: [Grete Hermann, givenName, Grete]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Grete
Context triple: [Grete Hermann, givenName, Grete]
  • A. Astrid
    Astrid is a Belgian princess and member of the country’s royal family.
  • B. Franziska
    Franziska is a feminine given name of German origin, closely related to and cognate with the name Frances.
  • C. Bettina
    Bettina is a feminine given name of Hebrew origin, often considered a diminutive of Elisabeth or Benedetta and used in various European languages.
  • D. Hilde
    Hilde is a feminine given name of Germanic origin, often associated with meanings related to battle or strength.
  • E. Fanny Koch
    Fanny Koch was the mother of Elsa Einstein, making her the maternal grandmother of physicist Albert Einstein.
  • 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: Grete
Triple: [Grete Hermann, givenName, Grete]
Generated description
Grete is the given name of Grete Hermann, a German mathematician and philosopher known for her pioneering work in the foundations of quantum mechanics and computer algebra.
NED2 Entity disambiguation (via description) gpt-5-mini-2025-08-07
Target entity: Grete
Target entity description: Grete is the given name of Grete Hermann, a German mathematician and philosopher known for her pioneering work in the foundations of quantum mechanics and computer algebra.
  • A. Werna Gerhardsen
    Werna Gerhardsen was a Norwegian politician and Labour Party activist, best known as the influential wife and political partner of long-serving prime minister Einar Gerhardsen.
  • B. Astrid
    Astrid is a Belgian princess and member of the country’s royal family.
  • C. Franziska
    Franziska is a feminine given name of German origin, closely related to and cognate with the name Frances.
  • D. Bettina
    Bettina is a feminine given name of Hebrew origin, often considered a diminutive of Elisabeth or Benedetta and used in various European languages.
  • E. Hilde
    Hilde is a feminine given name of Germanic origin, often associated with meanings related to battle or strength.
  • 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_69a498fb823c8190a67ce4c4837e641a completed March 1, 2026, 7:52 p.m.
NER Named-entity recognition batch_69a4c4915bfc8190a631330b7c495b49 completed March 1, 2026, 10:58 p.m.
NED1 Entity disambiguation (via context triple) batch_69ad015f5ad08190aaa0d1063432af2b completed March 8, 2026, 4:55 a.m.
NEDg Description generation batch_69ad01f8028881909af95e9f61a17e88 completed March 8, 2026, 4:58 a.m.
NED2 Entity disambiguation (via description) batch_69ad02c618c48190abf3e16d9f85e703 completed March 8, 2026, 5:01 a.m.
Created at: March 1, 2026, 8 p.m.