Triple

T1529863
Position Surface form Disambiguated ID Type / Status
Subject Bridgette Radebe E32415 entity
Predicate givenName P17 FINISHED
Object Bridgette
Bridgette is a feminine given name commonly used in English-speaking countries, often considered a variant of "Bridget."
 E214474 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: Bridgette | Statement: [Bridgette Radebe, givenName, Bridgette]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07 
Target entity: Bridgette
Context triple: [Bridgette Radebe, givenName, Bridgette]
  • A. Nicole
    Nicole is a central character in Margaret Atwood's dystopian novel "The Testaments," whose story helps expose and challenge the oppressive regime of Gilead.
  • B. Jacqueline
    Jacqueline is a feminine given name most famously borne by former U.S. First Lady Jacqueline Kennedy Onassis.
  • C. Adrianne
    Adrianne is a feminine given name most notably borne by American actress Adrianne Palicki.
  • D. Diane
    Diane is a feminine given name of Latin origin, derived from the name of the Roman goddess Diana.
  • E. Sandra
    Sandra is the given name of Sandra Day O’Connor, the first woman to serve as a Justice on the United States Supreme Court.
  • 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: Bridgette
Triple: [Bridgette Radebe, givenName, Bridgette]
Generated description
Bridgette is a feminine given name commonly used in English-speaking countries, often considered a variant of "Bridget."
NED2 Entity disambiguation (via description) gpt-5-mini-2025-08-07 
Target entity: Bridgette
Target entity description: Bridgette is a feminine given name commonly used in English-speaking countries, often considered a variant of "Bridget."
  • A. Nicole
    Nicole is a central character in Margaret Atwood's dystopian novel "The Testaments," whose story helps expose and challenge the oppressive regime of Gilead.
  • B. Jacqueline
    Jacqueline is a feminine given name most famously borne by former U.S. First Lady Jacqueline Kennedy Onassis.
  • C. Adrianne
    Adrianne is a feminine given name most notably borne by American actress Adrianne Palicki.
  • D. Diane
    Diane is a feminine given name of Latin origin, derived from the name of the Roman goddess Diana.
  • E. Sandra
    Sandra is the given name of Sandra Day O’Connor, the first woman to serve as a Justice on the United States Supreme Court.
  • 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_69a885ea86308190998f6bc14bb91f8e completed March 4, 2026, 7:20 p.m.
NER Named-entity recognition batch_69abb1dfd1a48190804ca5f0fb6f5985 completed March 7, 2026, 5:04 a.m.
NED1 Entity disambiguation (via context triple) batch_69adf3b2c2788190a22c3b45dedb1484 completed March 8, 2026, 10:09 p.m.
NEDg Description generation batch_69adf452ab488190b5d57e3b04159408 completed March 8, 2026, 10:12 p.m.
NED2 Entity disambiguation (via description) batch_69adf4bdb6dc8190964e5e78abfb8e40 completed March 8, 2026, 10:14 p.m.
Created at: March 4, 2026, 7:26 p.m.