Triple

T3136389
Position Surface form Disambiguated ID Type / Status
Subject Margit von Mises E65539 entity
Predicate givenName P17 FINISHED
Object Margit
Margit is the given name of Margit von Mises, an Austrian-American actress and writer best known as the wife and biographer of economist Ludwig von Mises.
 E113357 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: Margit | Statement: [Margit von Mises, givenName, Margit]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07 
Target entity: Margit
Context triple: [Margit von Mises, givenName, Margit]
  • A. Liesl
    Liesl is a feminine given name, commonly used as a diminutive of names like Elisabeth in German-speaking regions.
  • B. Jacoba
    Jacoba is a feminine given name of Dutch origin, historically borne by several notable women in the Netherlands and South Africa.
  • C. Margareta
    Margareta is a feminine given name used in various European languages, closely related to and derived from the name Margaret.
  • D. Margot
    Margot is a feminine given name of French origin, often associated with Margot Frank, the elder sister of diarist Anne Frank.
  • E. Margarida
    Margarida is a given name, commonly used in Portuguese and Catalan, that corresponds to the English name Margaret.
  • 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: Margit
Triple: [Margit von Mises, givenName, Margit]
Generated description
Margit is the given name of Margit von Mises, an Austrian-American actress and writer best known as the wife and biographer of economist Ludwig von Mises.
NED2 Entity disambiguation (via description) gpt-5-mini-2025-08-07 
Target entity: Margit
Target entity description: Margit is the given name of Margit von Mises, an Austrian-American actress and writer best known as the wife and biographer of economist Ludwig von Mises.
  • A. Liesl
    Liesl is a feminine given name, commonly used as a diminutive of names like Elisabeth in German-speaking regions.
  • B. Jacoba
    Jacoba is a feminine given name of Dutch origin, historically borne by several notable women in the Netherlands and South Africa.
  • C. Margareta chosen
    Margareta is a feminine given name used in various European languages, closely related to and derived from the name Margaret.
  • D. Margot
    Margot is a feminine given name of French origin, often associated with Margot Frank, the elder sister of diarist Anne Frank.
  • E. Margarida
    Margarida is a given name, commonly used in Portuguese and Catalan, that corresponds to the English name Margaret.
  • 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_69ad8581c25c8190b0d85ba9b9baa531 completed March 8, 2026, 2:19 p.m.
NER Named-entity recognition batch_69ada564eacc8190a54d07b4eb31c196 completed March 8, 2026, 4:35 p.m.
NED1 Entity disambiguation (via context triple) batch_69b20f8793488190aa31040edaf1d627 completed March 12, 2026, 12:57 a.m.
NEDg Description generation batch_69b2103d83688190b107ecbacac604c1 completed March 12, 2026, 1 a.m.
NED2 Entity disambiguation (via description) batch_69b210a290088190aaa10a015519e1de completed March 12, 2026, 1:02 a.m.
Created at: March 8, 2026, 3:05 p.m.