Triple

T38412696
Position Surface form Disambiguated ID Type / Status
Subject Anuradha (1960 film) E901519 entity
Predicate songFeatured P20452 FINISHED
Object Jaane Kaise Sapnon Mein
"Jaane Kaise Sapnon Mein" is a popular Hindi film song from the 1960 romantic drama *Anuradha*, known for its melodious composition and classic Bollywood charm.
E2268373 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: Jaane Kaise Sapnon Mein | Statement: [Anuradha (1960 film), songFeatured, Jaane Kaise Sapnon Mein]
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: Jaane Kaise Sapnon Mein
Triple: [Anuradha (1960 film), songFeatured, Jaane Kaise Sapnon Mein]
Generated description
"Jaane Kaise Sapnon Mein" is a popular Hindi film song from the 1960 romantic drama *Anuradha*, known for its melodious composition and classic Bollywood charm.

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_69f76e61e79c81908b787d83b46ab92b completed May 3, 2026, 3:48 p.m.
NER Named-entity recognition batch_69fccd6568fc8190a0a48aec8f3b0575 completed May 7, 2026, 5:35 p.m.
NED1 Entity disambiguation (via context triple) batch_6a41b2c2066481908fdb9cc5fc465666 completed June 28, 2026, 11:48 p.m.
NEDg Description generation batch_6a41b67584c48190840b9d38b56b44d8 completed June 29, 2026, 12:04 a.m.
NED2 Entity disambiguation (via description) batch_6a41b6ff98248190a5f18ded2db2295e completed June 29, 2026, 12:06 a.m.
Created at: May 3, 2026, 4:31 p.m.