Triple

T228970
Position Surface form Disambiguated ID Type / Status
Subject Emmy Noether E4369 entity
Predicate nickname P55 FINISHED
Object Emmy
Emmy is the affectionate nickname of Emmy Noether, the pioneering German mathematician renowned for her groundbreaking contributions to abstract algebra and theoretical physics.
 E29374 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: Emmy | Statement: [Emmy Noether, nickname, Emmy]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07 
Target entity: Emmy
Context triple: [Emmy Noether, nickname, Emmy]
  • A. Oscar
    The Oscar is a prestigious film industry award presented annually by the Academy of Motion Picture Arts and Sciences to honor outstanding cinematic achievements.
  • B. Nance
    Nance is the middle name of John Nance Garner, the 32nd vice president of the United States under Franklin D. Roosevelt.
  • C. Anna
    Anna is the given first name of Eleanor Roosevelt, the influential former First Lady of the United States and human rights advocate.
  • D. Barbara
    Barbara is a feminine given name of Greek origin that has been widely used in many cultures and languages.
  • E. Leslie
    Leslie is a small town in Fife, Scotland, situated near Glenrothes and known historically for its textile and papermaking industries.
  • 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: Emmy
Triple: [Emmy Noether, nickname, Emmy]
Generated description
Emmy is the affectionate nickname of Emmy Noether, the pioneering German mathematician renowned for her groundbreaking contributions to abstract algebra and theoretical physics.
NED2 Entity disambiguation (via description) gpt-5-mini-2025-08-07 
Target entity: Emmy
Target entity description: Emmy is the affectionate nickname of Emmy Noether, the pioneering German mathematician renowned for her groundbreaking contributions to abstract algebra and theoretical physics.
  • A. Oscar
    The Oscar is a prestigious film industry award presented annually by the Academy of Motion Picture Arts and Sciences to honor outstanding cinematic achievements.
  • B. Nance
    Nance is the middle name of John Nance Garner, the 32nd vice president of the United States under Franklin D. Roosevelt.
  • C. Anna
    Anna is the given first name of Eleanor Roosevelt, the influential former First Lady of the United States and human rights advocate.
  • D. Barbara
    Barbara is a feminine given name of Greek origin that has been widely used in many cultures and languages.
  • E. Leslie
    Leslie is a small town in Fife, Scotland, situated near Glenrothes and known historically for its textile and papermaking industries.
  • 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_69a257363ffc81909757bde7ab3404da completed Feb. 28, 2026, 2:47 a.m.
NER Named-entity recognition batch_69a25c9140c48190b90647400854b37e completed Feb. 28, 2026, 3:10 a.m.
NED1 Entity disambiguation (via context triple) batch_69a35b66359481908daf0412badd76bc completed Feb. 28, 2026, 9:17 p.m.
NEDg Description generation batch_69a35d280c8c81909dd05d5c45ffe616 completed Feb. 28, 2026, 9:24 p.m.
NED2 Entity disambiguation (via description) batch_69a35dc9ad808190a93a4a4c062ce69c completed Feb. 28, 2026, 9:27 p.m.
Created at: Feb. 28, 2026, 2:53 a.m.