Triple

T4651193
Position Surface form Disambiguated ID Type / Status
Subject Language Models are Few-Shot Learners E102297 entity
Predicate author P4 FINISHED
Object Pranav Shyam E457864 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: Pranav Shyam | Statement: [Language Models are Few-Shot Learners, author, Pranav Shyam]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Pranav Shyam
Context triple: [Language Models are Few-Shot Learners, author, Pranav Shyam]
  • A. Pranav Shyam chosen
    Pranav Shyam is a computer scientist and AI researcher known for co-authoring influential work in large-scale language models alongside Tom B. Brown and others.
  • B. Jaideep Ahlawat
    Jaideep Ahlawat is an Indian actor known for his powerful character roles in films and web series such as "Gangs of Wasseypur," "Raazi," and "Paatal Lok."
  • C. Sachit Mehra
    Sachit Mehra is a Canadian political figure who serves in a top leadership role within the Liberal Party of Canada.
  • D. Karthik Bala
    Karthik Bala is a video game developer and entrepreneur best known as the co-founder of the game studio Vicarious Visions.
  • E. 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.
  • F. None of above.
  • G. Unsure - the case is ambiguous/there is not enough information to decide.

Provenance (3 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_69bd43d71a308190afea7280841b0de8 completed March 20, 2026, 12:55 p.m.
NER Named-entity recognition batch_69bd630343f88190954d19fcd18a5864 completed March 20, 2026, 3:08 p.m.
NED1 Entity disambiguation (via context triple) batch_69be0374967c8190b77bcd3ea1c4d59d completed March 21, 2026, 2:33 a.m.
Created at: March 20, 2026, 1:14 p.m.