Triple

T20417794
Position Surface form Disambiguated ID Type / Status
Subject Shivam Tewari E500757 entity
Predicate hasRelativeByMarriage P7844 FINISHED
Object Suchitra Sen 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: Suchitra Sen | Statement: [Shivam Tewari, hasRelativeByMarriage, Suchitra Sen]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Suchitra Sen
Context triple: [Shivam Tewari, hasRelativeByMarriage, Suchitra Sen]
  • A. Suchitra Sen chosen
    Suchitra Sen was a legendary Indian film actress renowned for her powerful performances in Bengali cinema and as the first Indian actress to receive an international film award.
  • B. Aparna Sen
    Aparna Sen is an acclaimed Indian filmmaker, screenwriter, and actress known for her pioneering and nuanced work in Bengali cinema.
  • C. Sharmila Tagore
    Sharmila Tagore is an acclaimed Indian actress known for her influential work in both Bengali art cinema and mainstream Hindi films since the 1960s.
  • D. Sharmila Basu
    Sharmila Basu is a relatively obscure individual about whom no widely known public or biographical information is readily available.
  • E. Gita Sen
    Gita Sen is an Indian actress known for her frequent collaborations with her husband, acclaimed filmmaker Mrinal Sen, in Bengali parallel cinema.
  • 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_69e0b4a935588190b9446a99b37ced44 completed April 16, 2026, 10:06 a.m.
NER Named-entity recognition batch_69e67a44ecf48190ba5a3872af500dc8 completed April 20, 2026, 7:11 p.m.
Created at: April 16, 2026, 11:30 a.m.