Triple

T22756351
Position Surface form Disambiguated ID Type / Status
Subject Noor Pahlavi E562853 entity
Predicate givenName P17 FINISHED
Object Noor NE NERFINISHED

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: Noor | Statement: [Noor Pahlavi, givenName, Noor]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Noor
Context triple: [Noor Pahlavi, givenName, Noor]
  • A. Noor
    Noor is the American-born widow of King Hussein who served as Queen consort of Jordan and became known for her humanitarian and peace-building work.
  • B. Noor
    Noor is a science fiction novel by Nnedi Okorafor that blends Africanfuturism with themes of identity, technology, and survival in a near-future Nigeria.
  • C. Noor chosen
    Noor is a given name of Arabic origin meaning "light," used for both males and females in various cultures.
  • D. Nooran
    Nooran is a young Muslim woman in Khushwant Singh’s novel "Train to Pakistan," whose forbidden love with a Sikh man highlights the human cost of the Partition of India.
  • E. Noori
    Noori is a legendary female figure celebrated in Sindhi folklore and Sufi poetry as one of the Seven Queens immortalized by Shah Abdul Latif Bhittai for her humility and devotion.
  • F. None of above.
  • G. Unsure - the case is ambiguous/there is not enough information to decide.

Provenance (2 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_69e24551ec7881909a9c924dbea155f6 completed April 17, 2026, 2:36 p.m.
NER Named-entity recognition batch_69f179bd22588190ac724a656194f5b9 completed April 29, 2026, 3:23 a.m.
Created at: April 17, 2026, 3:25 p.m.