Triple

T1942134
Position Surface form Disambiguated ID Type / Status
Subject Rachael MacFarlane E41578 entity
Predicate givenName P17 FINISHED
Object Rachael
Rachael is a feminine given name commonly used in English-speaking countries, often considered a variant of the biblical name Rachel.
 E220850 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: Rachael | Statement: [Rachael MacFarlane, givenName, Rachael]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07 
Target entity: Rachael
Context triple: [Rachael MacFarlane, givenName, Rachael]
  • A. Rachele
    Rachele is an Italian given name, notably borne by Rachele Mussolini, the wife of dictator Benito Mussolini.
  • B. Charlene
    Charlene is a feminine given name derived from the male name Charles.
  • C. 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.
  • D. Diane
    Diane is a feminine given name of Latin origin, derived from the name of the Roman goddess Diana.
  • E. Bridgette
    Bridgette is a feminine given name commonly used in English-speaking countries, often considered a variant of "Bridget."
  • 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: Rachael
Triple: [Rachael MacFarlane, givenName, Rachael]
Generated description
Rachael is a feminine given name commonly used in English-speaking countries, often considered a variant of the biblical name Rachel.
NED2 Entity disambiguation (via description) gpt-5-mini-2025-08-07 
Target entity: Rachael
Target entity description: Rachael is a feminine given name commonly used in English-speaking countries, often considered a variant of the biblical name Rachel.
  • A. Rachele
    Rachele is an Italian given name, notably borne by Rachele Mussolini, the wife of dictator Benito Mussolini.
  • B. Charlene
    Charlene is a feminine given name derived from the male name Charles.
  • C. 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.
  • D. Diane
    Diane is a feminine given name of Latin origin, derived from the name of the Roman goddess Diana.
  • E. Bridgette
    Bridgette is a feminine given name commonly used in English-speaking countries, often considered a variant of "Bridget."
  • 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_69a88649b24c819080047f26b6db2ded completed March 4, 2026, 7:21 p.m.
NER Named-entity recognition batch_69abb2fc98e881909a539c0ebf842d8b completed March 7, 2026, 5:09 a.m.
NED1 Entity disambiguation (via context triple) batch_69adfbb7616881908bfc82997538ca08 completed March 8, 2026, 10:44 p.m.
NEDg Description generation batch_69adfc2b6a0c8190a9129dc0a930d1b1 completed March 8, 2026, 10:46 p.m.
NED2 Entity disambiguation (via description) batch_69adfd3ecb7881909a6692bb58211c2e completed March 8, 2026, 10:50 p.m.
Created at: March 4, 2026, 7:36 p.m.