Triple

T9193701
Position Surface form Disambiguated ID Type / Status
Subject Kanika Banerjee E220650 entity
Predicate alsoKnownAs P39 FINISHED
Object Kanika Bandyopadhyay E220650 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: Kanika Bandyopadhyay | Statement: [Kanika Banerjee, alsoKnownAs, Kanika Bandyopadhyay]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Kanika Bandyopadhyay
Context triple: [Kanika Banerjee, alsoKnownAs, Kanika Bandyopadhyay]
  • A. Kanika Banerjee chosen
    Kanika Banerjee was a renowned Indian Rabindra Sangeet vocalist celebrated for her emotive interpretations of Rabindranath Tagore’s songs.
  • B. Sutapa Sikdar
    Sutapa Sikdar is an Indian dialogue and screenplay writer best known as the wife of acclaimed actor Irrfan Khan.
  • C. Labanya Das
    Labanya Das was the wife of renowned Bengali poet Jibanananda Das and a figure associated with his personal and literary life.
  • D. Anuradha Banerjee
    Anuradha Banerjee is a notable individual distinguished enough to be recognized as a prominent bearer of the surname Banerjee.
  • E. Sutapa Dasgupta
    Sutapa Dasgupta is known as the wife of acclaimed Indian poet and National Award–winning filmmaker Buddhadeb Dasgupta.
  • 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_69ca83e7ba70819088b74866d9da2c30 completed March 30, 2026, 2:08 p.m.
NER Named-entity recognition batch_69ccd5c3614c81909e26417e00fdfa11 completed April 1, 2026, 8:22 a.m.
NED1 Entity disambiguation (via context triple) batch_69d065d5e81c8190b6687999a87fd559 completed April 4, 2026, 1:13 a.m.
Created at: March 30, 2026, 7:25 p.m.