Triple

T3875259
Position Surface form Disambiguated ID Type / Status
Subject Lauren Bacall E92485 entity
Predicate givenName P17 FINISHED
Object Betty
Betty is the birth name of iconic American actress Lauren Bacall, a legendary figure of Hollywood's Golden Age.
 E394650 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: Betty | Statement: [Lauren Bacall, givenName, Betty]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07 
Target entity: Betty
Context triple: [Lauren Bacall, givenName, Betty]
  • A. Betty
    Betty is a minor character in Enid Blyton’s "Malory Towers" series, known as a lively and mischievous schoolgirl at the boarding school.
  • B. Betty
    "Betty" is a renowned photorealistic painting by German artist Gerhard Richter, depicting his daughter turning away from the viewer and exemplifying his exploration of perception and representation.
  • C. Betty
    Betty is the nickname of Australian sprinter and four-time Olympic gold medalist Betty Cuthbert, famed for her dominance in the 1956 Melbourne Games.
  • D. Betty
    Betty is the young, resourceful heroine of the children's story "Betty's Bright Idea," known for her cleverness and problem-solving nature.
  • E. Betty
    Betty is the familiar nickname of Betty Ford, the former First Lady of the United States and founder of the Betty Ford Center for substance abuse treatment.
  • 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: Betty
Triple: [Lauren Bacall, givenName, Betty]
Generated description
Betty is the birth name of iconic American actress Lauren Bacall, a legendary figure of Hollywood's Golden Age.
NED2 Entity disambiguation (via description) gpt-5-mini-2025-08-07 
Target entity: Betty
Target entity description: Betty is the birth name of iconic American actress Lauren Bacall, a legendary figure of Hollywood's Golden Age.
  • A. Betty
    Betty is the familiar nickname of Betty Ford, the former First Lady of the United States and founder of the Betty Ford Center for substance abuse treatment.
  • B. Betty
    Betty is a feminine given name, often a diminutive of Elizabeth, that has been widely used in English-speaking countries.
  • C. Betty
    Betty is the nickname of Australian sprinter and four-time Olympic gold medalist Betty Cuthbert, famed for her dominance in the 1956 Melbourne Games.
  • D. Betty
    Betty is the childhood nickname of Elizabeth Parris, the young girl whose strange afflictions helped spark the Salem witch trials in 1692.
  • E. Betty
    Betty is the young, resourceful heroine of the children's story "Betty's Bright Idea," known for her cleverness and problem-solving nature.
  • 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_69aed967448c819086c4b358d37b25aa completed March 9, 2026, 2:29 p.m.
NER Named-entity recognition batch_69aeec706434819095e0d2b376adb548 completed March 9, 2026, 3:51 p.m.
NED1 Entity disambiguation (via context triple) batch_69b5124f095881909143b624128ff569 completed March 14, 2026, 7:46 a.m.
NEDg Description generation batch_69b512f4041081908eb32ae059681afa completed March 14, 2026, 7:49 a.m.
NED2 Entity disambiguation (via description) batch_69b5137200a08190bd2a78398e03803e completed March 14, 2026, 7:51 a.m.
Created at: March 9, 2026, 3:20 p.m.