Triple

T18317389
Position Surface form Disambiguated ID Type / Status
Subject Latifa bint Mohammed Al Maktoum E438783 entity
Predicate givenName P17 FINISHED
Object Latifa 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: Latifa | Statement: [Latifa bint Mohammed Al Maktoum, givenName, Latifa]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Latifa
Context triple: [Latifa bint Mohammed Al Maktoum, givenName, Latifa]
  • A. Latifa chosen
    Latifa is a young, imaginative girl character who serves as one of the official mascots of Expo 2020 Dubai, symbolizing innovation, curiosity, and the spirit of the event.
  • B. Madali Khan
    Madali Khan was a 19th-century ruler of the Kokand Khanate in Central Asia, known for his efforts to strengthen the state amid regional rivalries and Russian expansion.
  • C. Rehana
    Rehana is a character from the film "Desertion," serving as one of the central figures in its narrative of abandonment and emotional conflict.
  • D. Sufiya Zinobia
    Sufiya Zinobia is a central character in Salman Rushdie’s novel "Shame," symbolizing purity, repression, and the violent consequences of societal and familial pressures in a fictionalized Pakistan.
  • E. Farah Naaz
    Farah Naaz is an Indian film actress known for her prominent roles in Hindi cinema during the late 1980s and early 1990s.
  • 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_69d8b916a2d081909e249e4902f6aad9 completed April 10, 2026, 8:47 a.m.
NER Named-entity recognition batch_69e5021f5f1081909fd98c8fb786c7ff completed April 19, 2026, 4:26 p.m.
Created at: April 10, 2026, 10:36 a.m.