Triple

T1105640
Position Surface form Disambiguated ID Type / Status
Subject Life of Pi E25481 entity
Predicate leadActor P1507 FINISHED
Object Suraj Sharma
Suraj Sharma is an Indian actor best known for his breakout performance as the shipwrecked teenager Pi Patel in Ang Lee’s acclaimed film "Life of Pi."
E160313 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: Suraj Sharma | Statement: [Life of Pi, leadActor, Suraj Sharma]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Suraj Sharma
Context triple: [Life of Pi, leadActor, Suraj Sharma]
  • A. Nirvikar Singh
    Nirvikar Singh is an economist and academic known for his contributions to economic theory and policy, associated with leading institutions such as the Delhi School of Economics.
  • B. Nishant
    Nishant is a critically acclaimed 1975 Indian parallel cinema film directed by Shyam Benegal that explores themes of feudal oppression and social injustice in rural India.
  • C. Sachit Mehra
    Sachit Mehra is a Canadian political figure who serves in a top leadership role within the Liberal Party of Canada.
  • D. Rajat Monga
    Rajat Monga is a computer scientist and engineer best known as a co-creator and early lead of TensorFlow at Google Brain.
  • E. Vijay Kumar
    Vijay Kumar is a prominent roboticist and engineer known for his pioneering work in multi-robot systems and aerial robotics.
  • 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: Suraj Sharma
Triple: [Life of Pi, leadActor, Suraj Sharma]
Generated description
Suraj Sharma is an Indian actor best known for his breakout performance as the shipwrecked teenager Pi Patel in Ang Lee’s acclaimed film "Life of Pi."
NED2 Entity disambiguation (via description) gpt-5-mini-2025-08-07
Target entity: Suraj Sharma
Target entity description: Suraj Sharma is an Indian actor best known for his breakout performance as the shipwrecked teenager Pi Patel in Ang Lee’s acclaimed film "Life of Pi."
  • A. Nirvikar Singh
    Nirvikar Singh is an economist and academic known for his contributions to economic theory and policy, associated with leading institutions such as the Delhi School of Economics.
  • B. Nishant
    Nishant is a critically acclaimed 1975 Indian parallel cinema film directed by Shyam Benegal that explores themes of feudal oppression and social injustice in rural India.
  • C. Sachit Mehra
    Sachit Mehra is a Canadian political figure who serves in a top leadership role within the Liberal Party of Canada.
  • D. Rajat Monga
    Rajat Monga is a computer scientist and engineer best known as a co-creator and early lead of TensorFlow at Google Brain.
  • E. Vijay Kumar
    Vijay Kumar is a prominent roboticist and engineer known for his pioneering work in multi-robot systems and aerial robotics.
  • 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_69a49428d4448190b3b36991ceae87ce completed March 1, 2026, 7:31 p.m.
NER Named-entity recognition batch_69a4b9e21f048190bf4b63dd2c7c7641 completed March 1, 2026, 10:12 p.m.
NED1 Entity disambiguation (via context triple) batch_69acde0311d88190a3cd04c7e00253e2 completed March 8, 2026, 2:25 a.m.
NEDg Description generation batch_69acdfabfd3c8190960d8621b49284a8 completed March 8, 2026, 2:32 a.m.
NED2 Entity disambiguation (via description) batch_69ace0ea9d1c8190a73ed43b0a7bbd2f completed March 8, 2026, 2:37 a.m.
Created at: March 1, 2026, 7:43 p.m.