Triple

T7143172
Position Surface form Disambiguated ID Type / Status
Subject Upendra Bhanja E166499 entity
Predicate name P16 FINISHED
Object Upendra Bhanja E166499 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: Upendra Bhanja | Statement: [Upendra Bhanja, name, Upendra Bhanja]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Upendra Bhanja
Context triple: [Upendra Bhanja, name, Upendra Bhanja]
  • A. Upendra Bhanja chosen
    Upendra Bhanja was a celebrated 17th–18th century Odia poet renowned for his ornate style and major contributions to classical Odia literature.
  • B. Jagannath Mishra
    Jagannath Mishra was a Bengali Brahmin scholar and the father of the Vaishnava saint and reformer Chaitanya Mahaprabhu.
  • C. Nagendra Babu
    Nagendra Babu is an Indian film actor and producer primarily associated with Telugu cinema and the influential Konidela family film dynasty.
  • D. Kishore Sahu
    Kishore Sahu was a prominent Indian film director, actor, and producer known for his influential work during the Golden Age of Hindi cinema.
  • E. Ashok Chandra
    Ashok Chandra is a computer scientist known for his contributions to theoretical computer science and complexity theory.
  • 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_69c6888579d481909e05a8d6b81bf733 completed March 27, 2026, 1:39 p.m.
NER Named-entity recognition batch_69c6e779ace48190be9c33750e60a79e completed March 27, 2026, 8:24 p.m.
NED1 Entity disambiguation (via context triple) batch_69c7db01750c8190b8b147261be7d253 completed March 28, 2026, 1:43 p.m.
Created at: March 27, 2026, 2:46 p.m.