Triple

T7368736
Position Surface form Disambiguated ID Type / Status
Subject Pawan Kalyan E169936 entity
Predicate sibling P363 FINISHED
Object Nagendra Babu E637869 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: Nagendra Babu | Statement: [Pawan Kalyan, sibling, Nagendra Babu]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Nagendra Babu
Context triple: [Pawan Kalyan, sibling, Nagendra Babu]
  • A. Nagendra Babu chosen
    Nagendra Babu is an Indian film actor and producer primarily associated with Telugu cinema and the influential Konidela family film dynasty.
  • B. Manohar Raju
    Manohar Raju is an American attorney and criminal justice reform advocate who serves as the elected Public Defender of San Francisco.
  • C. D. Suresh Babu
    D. Suresh Babu is an Indian film producer and prominent figure in the Telugu cinema industry, known for heading Suresh Productions.
  • D. Narendra Mandal
    Narendra Mandal, also known as the Chamber of Princes, was a consultative assembly of the rulers of the princely states in British India, established to advise the colonial government on matters affecting their interests.
  • E. Kotagiri Venkateswara Rao
    Kotagiri Venkateswara Rao is a prominent Indian film editor known for his extensive work in Telugu cinema and collaborations on major blockbuster films.
  • 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_69c68a5ade988190885b7175f63b7534 completed March 27, 2026, 1:47 p.m.
NER Named-entity recognition batch_69c6f17fe278819094eb1dd886583c6a completed March 27, 2026, 9:07 p.m.
NED1 Entity disambiguation (via context triple) batch_69c87067b98081908439af85623a97ea completed March 29, 2026, 12:20 a.m.
Created at: March 27, 2026, 3:07 p.m.