Triple

T8738982
Position Surface form Disambiguated ID Type / Status
Subject Kaaka Muttai E207455 entity
Predicate writer P1360 FINISHED
Object M. Manikandan E780014 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: M. Manikandan | Statement: [Kaaka Muttai, writer, M. Manikandan]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: M. Manikandan
Context triple: [Kaaka Muttai, writer, M. Manikandan]
  • A. M. Manikandan chosen
    M. Manikandan is an Indian filmmaker and screenwriter known for his critically acclaimed Tamil films that blend social realism with subtle humor.
  • B. K. K. Senthil Kumar
    K. K. Senthil Kumar is an acclaimed Indian cinematographer best known for his visually stunning work in major Telugu films, including the epic Baahubali series.
  • C. R. Rathnavelu
    R. Rathnavelu is an acclaimed Indian cinematographer known for his visually striking work on major Tamil films, including collaborations with top directors and stars.
  • D. S. R. Kathir
    S. R. Kathir is an Indian cinematographer known for his visually striking work in Tamil cinema, particularly on acclaimed films like Subramaniapuram.
  • E. K. Karunakaran
    K. Karunakaran is an Indian academic administrator and professor who has served as the vice-chancellor of Bharathiar University in Tamil Nadu.
  • 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_69ca835a03a081909d4d4cd01a18c9fb completed March 30, 2026, 2:06 p.m.
NER Named-entity recognition batch_69cc5d470c8c81909ead395ef704c6ba completed March 31, 2026, 11:48 p.m.
NED1 Entity disambiguation (via context triple) batch_69d0542fccd081908e1359cc71ba6774 completed April 3, 2026, 11:58 p.m.
Created at: March 30, 2026, 6:38 p.m.