Triple

T8367202
Position Surface form Disambiguated ID Type / Status
Subject Riaad Moosa E197157 entity
Predicate spouse P13 FINISHED
Object Farzanah Moosa
Farzanah Moosa is best known as the wife of South African comedian and actor Riaad Moosa.
 E728160 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: Farzanah Moosa | Statement: [Riaad Moosa, spouse, Farzanah Moosa]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07 
Target entity: Farzanah Moosa
Context triple: [Riaad Moosa, spouse, Farzanah Moosa]
  • A. Marya Mojtahed-Zadeh
    Marya Mojtahed-Zadeh is an Iranian academic and political figure best known as the wife of former Iranian foreign minister Mohammad Javad Zarif.
  • B. Zahra Kazemi
    Zahra Kazemi was an Iranian-Canadian photojournalist whose death in Iranian custody in 2003 drew international condemnation and became a symbol of press repression and human rights abuses in Iran.
  • C. Delaram Ali
    Delaram Ali is an Iranian women's rights activist known for her prominent role in Iran’s One Million Signatures Campaign challenging discriminatory laws against women.
  • D. Zahra Sadeghi
    Zahra Sadeghi is an Iranian figure best known as the wife of former Iranian president Mohammad Khatami.
  • E. Sarah Solemani
    Sarah Solemani is a British actress and writer known for her roles in television comedies like "Him & Her" and "Bad Education" as well as various film and stage performances.
  • 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: Farzanah Moosa
Triple: [Riaad Moosa, spouse, Farzanah Moosa]
Generated description
Farzanah Moosa is best known as the wife of South African comedian and actor Riaad Moosa.
NED2 Entity disambiguation (via description) gpt-5-mini-2025-08-07 
Target entity: Farzanah Moosa
Target entity description: Farzanah Moosa is best known as the wife of South African comedian and actor Riaad Moosa.
  • A. Marya Mojtahed-Zadeh
    Marya Mojtahed-Zadeh is an Iranian academic and political figure best known as the wife of former Iranian foreign minister Mohammad Javad Zarif.
  • B. Zahra Kazemi
    Zahra Kazemi was an Iranian-Canadian photojournalist whose death in Iranian custody in 2003 drew international condemnation and became a symbol of press repression and human rights abuses in Iran.
  • C. Delaram Ali
    Delaram Ali is an Iranian women's rights activist known for her prominent role in Iran’s One Million Signatures Campaign challenging discriminatory laws against women.
  • D. Zahra Sadeghi
    Zahra Sadeghi is an Iranian figure best known as the wife of former Iranian president Mohammad Khatami.
  • E. Sarah Solemani
    Sarah Solemani is a British actress and writer known for her roles in television comedies like "Him & Her" and "Bad Education" as well as various film and stage performances.
  • 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_69ca82f2dbe48190aba982e75a0d94de completed March 30, 2026, 2:04 p.m.
NER Named-entity recognition batch_69cb808e56fc81908b5d37482f29452d completed March 31, 2026, 8:06 a.m.
NED1 Entity disambiguation (via context triple) batch_69cdc78c0c208190ba590c74512a4043 completed April 2, 2026, 1:34 a.m.
NEDg Description generation batch_69cdcc88456c8190ba8613b4cbf40fbb completed April 2, 2026, 1:55 a.m.
NED2 Entity disambiguation (via description) batch_69cdcd75714881908f0b069a94ee334f completed April 2, 2026, 1:59 a.m.
Created at: March 30, 2026, 6 p.m.