Triple

T21944751
Position Surface form Disambiguated ID Type / Status
Subject Virasat E541906 entity
Predicate basedOn P98 FINISHED
Object Thevar Magan NE NERFINISHED

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: Thevar Magan | Statement: [Virasat, basedOn, Thevar Magan]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Thevar Magan
Context triple: [Virasat, basedOn, Thevar Magan]
  • A. Thevar Magan chosen
    Thevar Magan is a critically acclaimed 1992 Tamil drama film, starring Kamal Haasan and Sivaji Ganesan, that explores themes of rural caste politics, family honor, and generational conflict.
  • B. Nayaka
    Nayaka refers to a South Indian-origin royal and warrior community historically influential in the politics and courts of Sri Lanka and southern India.
  • C. Karnan
    Karnan is a classic 1964 Tamil epic war film, starring Sivaji Ganesan as the Mahabharata hero Karna, renowned for its grand scale, powerful performances, and enduring cultural impact in Indian cinema.
  • D. Pandianadu
    Pandianadu is a Tamil-language action drama film known for its rural setting and intense storytelling, featuring filmmaker Bharathiraja in an acting role.
  • E. Vetrimaaran
    Vetrimaaran is an acclaimed Indian filmmaker and screenwriter known for his gritty, realistic Tamil-language films and multiple National Film Awards.
  • F. None of above.
  • G. Unsure - the case is ambiguous/there is not enough information to decide.

Provenance (2 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_69e0c47e2e5c81909a7f74ce3de50911 completed April 16, 2026, 11:14 a.m.
NER Named-entity recognition batch_69f1242688988190a7b8f033c49368de completed April 28, 2026, 9:18 p.m.
Created at: April 16, 2026, 7:56 p.m.