Triple

T21248588
Position Surface form Disambiguated ID Type / Status
Subject Fatma Neslişah Sultan E523681 entity
Predicate givenName P17 FINISHED
Object Fatma 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: Fatma | Statement: [Fatma Neslişah Sultan, givenName, Fatma]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Fatma
Context triple: [Fatma Neslişah Sultan, givenName, Fatma]
  • A. Fatima
    Fatima is a small community located on the Magdalen Islands in Quebec, Canada, known for its maritime setting and Acadian culture.
  • B. Fatima
    Fatima is a renowned Portuguese pilgrimage town famous for reported Marian apparitions and its major Catholic sanctuary.
  • C. Fatima
    Fatima is a desert woman in Paulo Coelho’s novel "The Alchemist," symbolizing true love and spiritual devotion that supports the protagonist’s quest.
  • D. Fatima chosen
    Fatima is a common female given name of Arabic origin, widely used in Muslim-majority cultures and historically associated with Fatimah, the daughter of the Prophet Muhammad.
  • E. Fatma Mohamed
    Fatma Mohamed is an actress best known for her recurring roles in Peter Strickland’s films, including the horror-comedy "In Fabric."
  • 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_69e0b5146c108190adc9adb73e90abff completed April 16, 2026, 10:08 a.m.
NER Named-entity recognition batch_69e7359b756c819085480ca4174c53c2 completed April 21, 2026, 8:30 a.m.
Created at: April 16, 2026, 3:56 p.m.