Triple

T12668465
Position Surface form Disambiguated ID Type / Status
Subject Raven-Symoné E302616 entity
Predicate spouse P13 FINISHED
Object Miranda Maday
Miranda Maday is a social media manager and producer best known as the wife of actress and singer Raven-Symoné.
 E994424 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: Miranda Maday | Statement: [Raven-Symoné, spouse, Miranda Maday]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07 
Target entity: Miranda Maday
Context triple: [Raven-Symoné, spouse, Miranda Maday]
  • A. Miranda Green
    Miranda Green is a British journalist and political commentator known for her analysis and appearances across UK broadcast media.
  • B. Miranda Greene
    Miranda Greene is a fictional character from the comedy film "King Ralph," where she serves as a key romantic interest and supporting figure in the story of an unlikely American who becomes the King of England.
  • C. Sylvia Miranda
    Sylvia Miranda is a notable individual recognized for bearing the surname Miranda, though specific widely known public details about her are limited.
  • D. Madelaine
    Madelaine is a character in the Danish crime thriller film "The Salvation."
  • E. Aurora Miranda
    Aurora Miranda was a Brazilian singer and actress, known for her vibrant musical performances in mid-20th-century films and for popularizing Brazilian music internationally.
  • 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: Miranda Maday
Triple: [Raven-Symoné, spouse, Miranda Maday]
Generated description
Miranda Maday is a social media manager and producer best known as the wife of actress and singer Raven-Symoné.
NED2 Entity disambiguation (via description) gpt-5-mini-2025-08-07 
Target entity: Miranda Maday
Target entity description: Miranda Maday is a social media manager and producer best known as the wife of actress and singer Raven-Symoné.
  • A. Miranda Green
    Miranda Green is a British journalist and political commentator known for her analysis and appearances across UK broadcast media.
  • B. Miranda Greene
    Miranda Greene is a fictional character from the comedy film "King Ralph," where she serves as a key romantic interest and supporting figure in the story of an unlikely American who becomes the King of England.
  • C. Sylvia Miranda
    Sylvia Miranda is a notable individual recognized for bearing the surname Miranda, though specific widely known public details about her are limited.
  • D. Madelaine
    Madelaine is a character in the Danish crime thriller film "The Salvation."
  • E. Aurora Miranda
    Aurora Miranda was a Brazilian singer and actress, known for her vibrant musical performances in mid-20th-century films and for popularizing Brazilian music internationally.
  • 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_69d7bded71a88190bb76e2413af9ea66 completed April 9, 2026, 2:55 p.m.
NER Named-entity recognition batch_69d96181c40481908f3e2717f5472b85 completed April 10, 2026, 8:45 p.m.
NED1 Entity disambiguation (via context triple) batch_69f6688bfc048190970d281e66c34cdc completed May 2, 2026, 9:11 p.m.
NEDg Description generation batch_69f6695372688190b09a2bb2e58cb546 completed May 2, 2026, 9:14 p.m.
NED2 Entity disambiguation (via description) batch_69f669fe4bc48190adba50ad58b10c45 completed May 2, 2026, 9:17 p.m.
Created at: April 9, 2026, 5:20 p.m.