Triple

T19937258
Position Surface form Disambiguated ID Type / Status
Subject M. K. Stalin E479203 entity
Predicate child P120 FINISHED
Object Udhayanidhi Stalin 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: Udhayanidhi Stalin | Statement: [M. K. Stalin, child, Udhayanidhi Stalin]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Udhayanidhi Stalin
Context triple: [M. K. Stalin, child, Udhayanidhi Stalin]
  • A. Udhayanidhi Stalin chosen
    Udhayanidhi Stalin is an Indian film producer, actor, and politician from Tamil Nadu, known for his work in Tamil cinema and his role in the Dravida Munnetra Kazhagam (DMK) party.
  • B. M. K. Stalin
    M. K. Stalin is an Indian politician serving as the Chief Minister of Tamil Nadu and a prominent leader of the Dravidian movement.
  • C. Veeru Krishnan
    Veeru Krishnan was an Indian actor and classical dance teacher best known for his comic and character roles in Hindi films during the 1990s.
  • D. Anbumani Ramadoss
    Anbumani Ramadoss is an Indian politician and former Union Health Minister, known for his leadership in the Pattali Makkal Katchi (PMK) party and his public health advocacy.
  • E. K. Balaji
    K. Balaji was an Indian film producer and actor known for his work in Tamil cinema and for producing several successful remakes of Hindi films.
  • 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_69d8e522a17c819095165d4d24939fd8 completed April 10, 2026, 11:55 a.m.
NER Named-entity recognition batch_69e65a17fb2c8190b3aaae88e741648a completed April 20, 2026, 4:53 p.m.
Created at: April 10, 2026, 1:53 p.m.