Triple

T9909718
Position Surface form Disambiguated ID Type / Status
Subject Ranbir Kapoor E185108 entity
Predicate spouse P13 FINISHED
Object Alia Bhatt E637873 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: Alia Bhatt | Statement: [Ranbir Kapoor, spouse, Alia Bhatt]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Alia Bhatt
Context triple: [Ranbir Kapoor, spouse, Alia Bhatt]
  • A. Alia Bhatt chosen
    Alia Bhatt is a prominent Indian actress known for her versatile performances in Hindi cinema and for being one of the leading contemporary stars of Bollywood.
  • B. Deepika Padukone
    Deepika Padukone is a leading Indian film actress and producer, internationally recognized for her work in Bollywood and Hollywood as well as her advocacy for mental health awareness.
  • C. Samantha Ruth Prabhu
    Samantha Ruth Prabhu is a prominent Indian actress known for her leading roles in Telugu and Tamil cinema and for being one of South India's most popular and acclaimed film stars.
  • D. Anushka Sharma
    Anushka Sharma is a prominent Indian actress and film producer known for her work in Bollywood films such as "Rab Ne Bana Di Jodi," "PK," and "NH10."
  • E. Kangana Ranaut
    Kangana Ranaut is an acclaimed Indian film actress known for her powerful performances in Hindi cinema and multiple National Film Awards.
  • 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_69ca8296165881908ca4750701af1f29 completed March 30, 2026, 2:03 p.m.
NER Named-entity recognition batch_69cdb51184d08190a0350f2722110811 completed April 2, 2026, 12:15 a.m.
NED1 Entity disambiguation (via context triple) batch_69d20db5979081909b8e292ac6bb7c2f completed April 5, 2026, 7:22 a.m.
Created at: March 30, 2026, 8:41 p.m.