Triple

T16183233
Position Surface form Disambiguated ID Type / Status
Subject Mohammed Aamir Hussain Khan E392736 entity
Predicate spouse P13 FINISHED
Object Kiran Rao E392746 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: Kiran Rao | Statement: [Mohammed Aamir Hussain Khan, spouse, Kiran Rao]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Kiran Rao
Context triple: [Mohammed Aamir Hussain Khan, spouse, Kiran Rao]
  • A. Kiran Rao chosen
    Kiran Rao is an Indian film producer, director, and screenwriter known for her work in Hindi cinema and for co-producing acclaimed films such as "Dhobi Ghat" and "Delhi Belly."
  • B. Surekha Konidela
    Surekha Konidela is an Indian film producer and member of the prominent Allu–Konidela family in the Telugu cinema industry.
  • C. Samantha Akkineni
    Samantha Akkineni is a prominent Indian actress known for her acclaimed performances in Telugu and Tamil cinema, as well as her work in several successful pan-Indian projects.
  • D. Ramya Krishnan
    Ramya Krishnan is an acclaimed Indian actress known for her powerful and versatile performances across Tamil, Telugu, and other South Indian film industries.
  • E. Sobhita Dhulipala
    Sobhita Dhulipala is an Indian actress and former model known for her work in Hindi cinema and streaming series such as "Made in Heaven."
  • 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_69d87f1e49ac8190a311b54d32990576 completed April 10, 2026, 4:39 a.m.
NER Named-entity recognition batch_69e2205ef39081908da383abdebc2ccc completed April 17, 2026, 11:58 a.m.
NED1 Entity disambiguation (via context triple) batch_69ffff03400481908e66db8cf0213c15 completed May 10, 2026, 3:44 a.m.
Created at: April 10, 2026, 5:02 a.m.