Triple

T13517389
Position Surface form Disambiguated ID Type / Status
Subject Googie Withers E322799 entity
Predicate givenName P17 FINISHED
Object Georgette
Georgette is the given name of British actress Googie Withers, who was born Georgette Lizette Withers.
 E1046030 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: Georgette | Statement: [Googie Withers, givenName, Georgette]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07 
Target entity: Georgette
Context triple: [Googie Withers, givenName, Georgette]
  • A. Georgette
    Georgette is a comic servant character in Molière’s play "L’École des femmes," known for her earthy wit and role in highlighting the play’s social and gender tensions.
  • B. Louise
    Louise is an opera by French composer Gustave Charpentier, renowned for its realistic portrayal of Parisian working-class life and its influential role in early 20th-century French opera.
  • C. Louise
    Louise is a feminine given name of French origin, traditionally associated with nobility and widely used in many European and English-speaking countries.
  • D. Madeleine
    Madeleine is a feminine given name, commonly used in French and English, derived from Magdalene and often associated with literary and cultural figures.
  • E. Madeleine
    Madeleine is a Paris Métro station in central Paris that serves as an interchange between several metro lines, including the automated Line 14.
  • 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: Georgette
Triple: [Googie Withers, givenName, Georgette]
Generated description
Georgette is the given name of British actress Googie Withers, who was born Georgette Lizette Withers.
NED2 Entity disambiguation (via description) gpt-5-mini-2025-08-07 
Target entity: Georgette
Target entity description: Georgette is the given name of British actress Googie Withers, who was born Georgette Lizette Withers.
  • A. Georgette
    Georgette is a comic servant character in Molière’s play "L’École des femmes," known for her earthy wit and role in highlighting the play’s social and gender tensions.
  • B. Louise
    Louise is a feminine given name of French origin, traditionally associated with nobility and widely used in many European and English-speaking countries.
  • C. Louise
    Louise is an opera by French composer Gustave Charpentier, renowned for its realistic portrayal of Parisian working-class life and its influential role in early 20th-century French opera.
  • D. Madeleine
    Madeleine is a feminine given name, commonly used in French and English, derived from Magdalene and often associated with literary and cultural figures.
  • E. Madeleine
    Madeleine is a Paris Métro station in central Paris that serves as an interchange between several metro lines, including the automated Line 14.
  • 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_69d80766a21881909f21a1b7421d3b8a completed April 9, 2026, 8:09 p.m.
NER Named-entity recognition batch_69dbafa27f048190bed33a98e28c8d09 completed April 12, 2026, 2:43 p.m.
NED1 Entity disambiguation (via context triple) batch_69f75d93a2608190a3a693bf4086a010 completed May 3, 2026, 2:37 p.m.
NEDg Description generation batch_69f75ed5457c819093081c6a22f13c91 completed May 3, 2026, 2:42 p.m.
NED2 Entity disambiguation (via description) batch_69f75f7e9d2c81909ec5540b34ac97cb completed May 3, 2026, 2:45 p.m.
Created at: April 9, 2026, 9:44 p.m.