Triple

T13002708
Position Surface form Disambiguated ID Type / Status
Subject Below Deck E322207 entity
Predicate executiveProducer P7225 FINISHED
Object Nadine Rajabi E943750 NE FINISHED

How this triple was built (2 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: Nadine Rajabi | Statement: [Below Deck, executiveProducer, Nadine Rajabi]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Nadine Rajabi
Context triple: [Below Deck, executiveProducer, Nadine Rajabi]
  • A. Nadine Rajabi chosen
    Nadine Rajabi is a Canadian-born comedian, television writer, and producer known for her work in stand-up and on various comedy and reality TV projects.
  • B. Sussan Tahmasebi
    Sussan Tahmasebi is an Iranian women's rights activist and civil society leader known for her advocacy against discriminatory laws and her role in grassroots reform movements.
  • C. Sediqa Massoud
    Sediqa Massoud is the widow of famed Afghan resistance leader Ahmad Shah Massoud and a prominent advocate for women's rights and education in Afghanistan.
  • D. Mina Badie
    Mina Badie is an American actress known for her character roles in film and television, and for being part of a family of performers that includes her sister Jennifer Jason Leigh.
  • 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.
  • G. Unsure - the case is ambiguous/there is not enough information to decide.

Provenance (3 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_69d807657e8c8190bd9435ee2f823845 completed April 9, 2026, 8:09 p.m.
NER Named-entity recognition batch_69d97e9a2a448190968833354280e474 completed April 10, 2026, 10:50 p.m.
NED1 Entity disambiguation (via context triple) batch_69f6cbc5c9a88190b70bda472bf3b062 completed May 3, 2026, 4:15 a.m.
Created at: April 9, 2026, 8:47 p.m.