Triple

T4902772
Position Surface form Disambiguated ID Type / Status
Subject Lauren Beukes E109840 entity
Predicate givenName P17 FINISHED
Object Lauren
Lauren is a common given name used for people of any gender in various English-speaking and other countries.
 E478716 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: Lauren | Statement: [Lauren Beukes, givenName, Lauren]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07 
Target entity: Lauren
Context triple: [Lauren Beukes, givenName, Lauren]
  • A. Lauren
    Lauren is a central female protagonist in the romantic comedy film "Think Like a Man," portrayed as a successful, relationship-seeking woman whose love life is influenced by Steve Harvey’s dating advice.
  • B. Lauren
    Lauren is a central character in the musical "Kinky Boots," known as a quirky, down-to-earth factory worker who becomes a key ally and love interest to the protagonist.
  • C. Laurene
    Laurene is the first name of Laurene Powell Jobs, an American businesswoman, philanthropist, and widow of Apple co-founder Steve Jobs.
  • D. Laurie
    Laurie is a character from the horror film "Night Monster," involved in the eerie and suspenseful events surrounding the mysterious killings at the Ingston estate.
  • E. Laurie
    Laurie is a charming, wealthy, and impulsive young man who becomes a close friend and would-be suitor to the March sisters in Louisa May Alcott’s novel "Little Women."
  • 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: Lauren
Triple: [Lauren Beukes, givenName, Lauren]
Generated description
Lauren is a common given name used for people of any gender in various English-speaking and other countries.
NED2 Entity disambiguation (via description) gpt-5-mini-2025-08-07 
Target entity: Lauren
Target entity description: Lauren is a common given name used for people of any gender in various English-speaking and other countries.
  • A. Lauren
    Lauren is a central female protagonist in the romantic comedy film "Think Like a Man," portrayed as a successful, relationship-seeking woman whose love life is influenced by Steve Harvey’s dating advice.
  • B. Lauren
    Lauren is a central character in the musical "Kinky Boots," known as a quirky, down-to-earth factory worker who becomes a key ally and love interest to the protagonist.
  • C. Laurene
    Laurene is the first name of Laurene Powell Jobs, an American businesswoman, philanthropist, and widow of Apple co-founder Steve Jobs.
  • D. Laurie
    Laurie is a character from the horror film "Night Monster," involved in the eerie and suspenseful events surrounding the mysterious killings at the Ingston estate.
  • E. Laurie
    Laurie is a charming, wealthy, and impulsive young man who becomes a close friend and would-be suitor to the March sisters in Louisa May Alcott’s novel "Little Women."
  • 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_69bd441180708190ba42ffb44fea533a completed March 20, 2026, 12:56 p.m.
NER Named-entity recognition batch_69bd6e4f1fd4819092812504c3529cad completed March 20, 2026, 3:57 p.m.
NED1 Entity disambiguation (via context triple) batch_69be6fd6ce008190ae7897bc58a2e786 completed March 21, 2026, 10:15 a.m.
NEDg Description generation batch_69be70752384819088ce3b6d00dd166a completed March 21, 2026, 10:18 a.m.
NED2 Entity disambiguation (via description) batch_69be7126d1648190b3b0aa89891f02df completed March 21, 2026, 10:21 a.m.
Created at: March 20, 2026, 1:28 p.m.