Triple

T11102753
Position Surface form Disambiguated ID Type / Status
Subject Karisma Kapoor E262551 entity
Predicate notableWork P4 FINISHED
Object Fiza E694867 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: Fiza | Statement: [Karisma Kapoor, notableWork, Fiza]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Fiza
Context triple: [Karisma Kapoor, notableWork, Fiza]
  • A. Fiza chosen
    Fiza is a 2000 Indian Hindi-language crime drama film directed by Khalid Mohammed, known for its intense portrayal of a sister’s search for her missing brother against the backdrop of communal violence.
  • B. Shareefa
    Shareefa is an American R&B singer best known for her mid-2000s work with Ludacris’s Disturbing tha Peace label, including the hit single "Need a Boss."
  • C. Ayesha
    Ayesha is a central fictional heroine in Bankim Chandra Chattopadhyay’s historical Bengali novel "Durgeshnandini," known for her beauty, courage, and tragic love.
  • D. Unaizah
    Unaizah is a historic oasis city in central Saudi Arabia’s Qassim region, known for its date farms, traditional markets, and cultural heritage.
  • E. Zohra
    Zohra is a character in Naguib Mahfouz’s novel "Miramar," which centers on the lives and conflicts of residents in a pension in Alexandria, Egypt.
  • 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_69d6aa9a40d88190a373e2c7e48285db completed April 8, 2026, 7:20 p.m.
NER Named-entity recognition batch_69d79a2c30a481908c45020c37caebe4 completed April 9, 2026, 12:23 p.m.
NED1 Entity disambiguation (via context triple) batch_69e3e7f9b46881909761ed448fa5ce6e completed April 18, 2026, 8:22 p.m.
Created at: April 8, 2026, 9:27 p.m.