Triple

T239550
Position Surface form Disambiguated ID Type / Status
Subject Bettina Aptheker E4897 entity
Predicate givenName P17 FINISHED
Object Bettina
Bettina is a feminine given name of Hebrew origin, often considered a diminutive of Elisabeth or Benedetta and used in various European languages.
 E36497 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: Bettina | Statement: [Bettina Aptheker, givenName, Bettina]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07 
Target entity: Bettina
Context triple: [Bettina Aptheker, givenName, Bettina]
  • A. Anna von Bönninghausen
    Anna von Bönninghausen was a 17th-century German noblewoman best known as the mother of Bernhard von Galen, the influential Prince-Bishop of Münster.
  • B. Amalie
    Amalie is the given first name of the pioneering German mathematician Emmy Noether, renowned for her foundational contributions to abstract algebra and theoretical physics.
  • C. Marie
    Marie is a widely used European given name, especially common in French-speaking countries, derived from the Hebrew name Miryam (Mary).
  • D. Estelle
    Estelle is a British singer, rapper, and songwriter best known for her hit single "American Boy" featuring Kanye West.
  • E. Louise
    Louise is a feminine given name of French origin, traditionally associated with nobility and widely used in many European and English-speaking countries.
  • 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: Bettina
Triple: [Bettina Aptheker, givenName, Bettina]
Generated description
Bettina is a feminine given name of Hebrew origin, often considered a diminutive of Elisabeth or Benedetta and used in various European languages.
NED2 Entity disambiguation (via description) gpt-5-mini-2025-08-07 
Target entity: Bettina
Target entity description: Bettina is a feminine given name of Hebrew origin, often considered a diminutive of Elisabeth or Benedetta and used in various European languages.
  • A. Anna von Bönninghausen
    Anna von Bönninghausen was a 17th-century German noblewoman best known as the mother of Bernhard von Galen, the influential Prince-Bishop of Münster.
  • B. Amalie
    Amalie is the given first name of the pioneering German mathematician Emmy Noether, renowned for her foundational contributions to abstract algebra and theoretical physics.
  • C. Marie
    Marie is a widely used European given name, especially common in French-speaking countries, derived from the Hebrew name Miryam (Mary).
  • D. Estelle
    Estelle is a British singer, rapper, and songwriter best known for her hit single "American Boy" featuring Kanye West.
  • E. Louise
    Louise is a feminine given name of French origin, traditionally associated with nobility and widely used in many European and English-speaking countries.
  • 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_69a257c3d0708190b0871c4269d273e6 completed Feb. 28, 2026, 2:49 a.m.
NER Named-entity recognition batch_69a25ceaecdc81909e9ff49cb6a4e02a completed Feb. 28, 2026, 3:11 a.m.
NED1 Entity disambiguation (via context triple) batch_69a3949e1e2c819092c702b1fa1cb46c completed March 1, 2026, 1:21 a.m.
NEDg Description generation batch_69a3986c9b648190a1c30de3b0b52da6 completed March 1, 2026, 1:37 a.m.
NED2 Entity disambiguation (via description) batch_69a398c6b6588190a4213b66f07471b2 completed March 1, 2026, 1:39 a.m.
Created at: Feb. 28, 2026, 2:53 a.m.