Triple

T29314740
Position Surface form Disambiguated ID Type / Status
Subject Mr. India E743345 entity
Predicate notableQuote P492 FINISHED
Object Mogambo khush hua
"Mogambo khush hua" is an iconic Hindi film catchphrase delivered by the villain Mogambo in the 1987 Bollywood movie *Mr. India*, symbolizing his sinister satisfaction and becoming a staple of Indian pop culture.
E1862135 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: Mogambo khush hua | Statement: [Mr. India, notableQuote, Mogambo khush hua]
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: Mogambo khush hua
Triple: [Mr. India, notableQuote, Mogambo khush hua]
Generated description
"Mogambo khush hua" is an iconic Hindi film catchphrase delivered by the villain Mogambo in the 1987 Bollywood movie *Mr. India*, symbolizing his sinister satisfaction and becoming a staple of Indian pop culture.

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_69f0912502c8819087d9e8398ee991a8 completed April 28, 2026, 10:51 a.m.
NER Named-entity recognition batch_69f665ea0a8c8190a0c50c44cec4d9bb completed May 2, 2026, 9 p.m.
NED1 Entity disambiguation (via context triple) batch_6a25a86c38fc819086372adeade1e263 completed June 7, 2026, 5:20 p.m.
NEDg Description generation batch_6a25accca754819087850f98ba074aeb completed June 7, 2026, 5:39 p.m.
NED2 Entity disambiguation (via description) batch_6a25b13620148190ab87852c2312d21f completed June 7, 2026, 5:58 p.m.
Created at: April 28, 2026, 1:19 p.m.