Triple

T5693880
Position Surface form Disambiguated ID Type / Status
Subject Irrfan Khan E125488 entity
Predicate notableWork P4 FINISHED
Object Billu
Billu is a 2009 Indian Hindi-language comedy-drama film about a poor village barber whose life changes when a Bollywood superstar, played by Shah Rukh Khan, visits his town.
 E541899 NE FINISHED

How this triple was built (4 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: Billu | Statement: [Irrfan Khan, notableWork, Billu]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07 
Target entity: Billu
Context triple: [Irrfan Khan, notableWork, Billu]
  • A. Badal
    Badal is a Barcelona Metro station that serves the area near Camp Nou stadium in Barcelona, Spain.
  • B. Bughotu
    Bughotu is an Austronesian language spoken by communities on Santa Isabel Island in the Solomon Islands.
  • C. Yannai
    Yannai is another name for Alexander Jannaeus, a Hasmonean king of Judea and high priest who ruled in the early 1st century BCE.
  • D. Chholiya
    Chholiya is a traditional folk dance of the Kumaon region of Uttarakhand, India, often performed at weddings and festivals and characterized by its sword-and-shield martial style.
  • E. Gaga Bhatt
    Gaga Bhatt was a prominent 17th-century Hindu scholar and priest from Varanasi, best known for officiating the royal coronation of the Maratha ruler Shivaji.
  • F. None of above. chosen
  • G. Unsure - the case is ambiguous/there is not enough information to decide.
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: Billu
Triple: [Irrfan Khan, notableWork, Billu]
Generated description
Billu is a 2009 Indian Hindi-language comedy-drama film about a poor village barber whose life changes when a Bollywood superstar, played by Shah Rukh Khan, visits his town.
NED2 Entity disambiguation (via description) gpt-5-mini-2025-08-07 
Target entity: Billu
Target entity description: Billu is a 2009 Indian Hindi-language comedy-drama film about a poor village barber whose life changes when a Bollywood superstar, played by Shah Rukh Khan, visits his town.
  • A. Badal
    Badal is a Barcelona Metro station that serves the area near Camp Nou stadium in Barcelona, Spain.
  • B. Bughotu
    Bughotu is an Austronesian language spoken by communities on Santa Isabel Island in the Solomon Islands.
  • C. Yannai
    Yannai is another name for Alexander Jannaeus, a Hasmonean king of Judea and high priest who ruled in the early 1st century BCE.
  • D. Chholiya
    Chholiya is a traditional folk dance of the Kumaon region of Uttarakhand, India, often performed at weddings and festivals and characterized by its sword-and-shield martial style.
  • E. Gaga Bhatt
    Gaga Bhatt was a prominent 17th-century Hindu scholar and priest from Varanasi, best known for officiating the royal coronation of the Maratha ruler Shivaji.
  • F. None of above. chosen

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_69c0082bb19c8190823a4facd3cba79b completed March 22, 2026, 3:18 p.m.
NER Named-entity recognition batch_69c023e7dbe48190850b501f223614e3 completed March 22, 2026, 5:16 p.m.
NED1 Entity disambiguation (via context triple) batch_69c05a528a348190a7f6fd4cc3b76c92 completed March 22, 2026, 9:08 p.m.
NEDg Description generation batch_69c05d8890148190a4f81b2c1ca70886 completed March 22, 2026, 9:22 p.m.
NED2 Entity disambiguation (via description) batch_69c0620ee1848190935f5f78abbed7ba completed March 22, 2026, 9:41 p.m.
Created at: March 22, 2026, 3:44 p.m.