Triple

T33499067
Position Surface form Disambiguated ID Type / Status
Subject Kasautii Zindagii Kay E857939 entity
Predicate portrayedBy P1507 FINISHED
Object Urvashi Dholakia
Urvashi Dholakia is an Indian television actress best known for her iconic role as the antagonist Komolika in the popular Hindi soap opera "Kasautii Zindagii Kay."
E2222315 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: Urvashi Dholakia | Statement: [Kasautii Zindagii Kay, portrayedBy, Urvashi Dholakia]
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: Urvashi Dholakia
Triple: [Kasautii Zindagii Kay, portrayedBy, Urvashi Dholakia]
Generated description
Urvashi Dholakia is an Indian television actress best known for her iconic role as the antagonist Komolika in the popular Hindi soap opera "Kasautii Zindagii Kay."

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_69f3497660508190a541826a81f7e9ab completed April 30, 2026, 12:22 p.m.
NER Named-entity recognition batch_69f6e56e373481909502b961265cd68d completed May 3, 2026, 6:04 a.m.
NED1 Entity disambiguation (via context triple) batch_6a40636838e4819090536a5245e53ac5 completed June 27, 2026, 11:57 p.m.
NEDg Description generation batch_6a4064ff3f5c8190903b3c4ccf87b35d completed June 28, 2026, 12:04 a.m.
NED2 Entity disambiguation (via description) batch_6a406574585c8190a8d9f3565bdd46ea completed June 28, 2026, 12:06 a.m.
Created at: May 1, 2026, 1:38 a.m.