Triple

T38536861
Position Surface form Disambiguated ID Type / Status
Subject Kapoor & Sons E924724 entity
Predicate mainCharacter P1183 FINISHED
Object Rahul Kapoor
Rahul Kapoor is a central protagonist in the Hindi family drama film "Kapoor & Sons," portrayed as a successful yet emotionally conflicted member of the Kapoor family.
E2286279 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: Rahul Kapoor | Statement: [Kapoor & Sons, mainCharacter, Rahul Kapoor]
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: Rahul Kapoor
Triple: [Kapoor & Sons, mainCharacter, Rahul Kapoor]
Generated description
Rahul Kapoor is a central protagonist in the Hindi family drama film "Kapoor & Sons," portrayed as a successful yet emotionally conflicted member of 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_69f76eadeac081909cdfdd0474cb6765 completed May 3, 2026, 3:50 p.m.
NER Named-entity recognition batch_69fcd2e718088190912c2e47fbaf15cb completed May 7, 2026, 5:59 p.m.
NED1 Entity disambiguation (via context triple) batch_6a465ea4b0b081908bbc72cde3eed0ec completed July 2, 2026, 12:50 p.m.
NEDg Description generation batch_6a465f37d78081909f4cdede5eae3ef6 completed July 2, 2026, 12:53 p.m.
NED2 Entity disambiguation (via description) batch_6a469d2b95548190aabde4ef0e5f84ed completed July 2, 2026, 5:17 p.m.
Created at: May 3, 2026, 4:32 p.m.