Triple

T33626361
Position Surface form Disambiguated ID Type / Status
Subject Rhea Kapoor E861414 entity
Predicate spouse P13 FINISHED
Object Karan Boolani
Karan Boolani is an Indian filmmaker and producer known for his work in Hindi cinema and his collaborations with the Kapoor family.
E2060646 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: Karan Boolani | Statement: [Rhea Kapoor, spouse, Karan Boolani]
NEDg Description generation gpt-5.1
Instruction
Generate a one-sentence description of the target entity. 
You are given a context triple in the form (subject, predicate, object), where the object is the target entity. 
# Instructions
Use the triple to infer relevant information about the entity. Describe the entity based on what is most defining, well-known. 
Avoid repeating the information from the triple, unless really essential.
# Response Format
Return only the sentence: "Description: [one-sentence description of the target entity]"
Input
Entity: Karan Boolani
Triple: [Rhea Kapoor, spouse, Karan Boolani]
Generated description
Karan Boolani is an Indian filmmaker and producer known for his work in Hindi cinema and his collaborations with the Kapoor family.

Provenance (5 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_69f34981c54c81909b33c3fa2208a52d completed April 30, 2026, 12:22 p.m.
NER Named-entity recognition batch_69f6f85724048190be13f0503898a67e completed May 3, 2026, 7:25 a.m.
NED1 Entity disambiguation (via context triple) batch_6a36271510a08190960b75f75ddd7f5b completed June 20, 2026, 5:37 a.m.
NEDg Description generation batch_6a3627bba8bc81909091699b621fd31b completed June 20, 2026, 5:40 a.m.
NED2 Entity disambiguation (via description) batch_6a3628683bac81908b766d3154f2188d completed June 20, 2026, 5:43 a.m.
Created at: May 1, 2026, 1:41 a.m.