Triple

T6969375
Position Surface form Disambiguated ID Type / Status
Subject Mythri Movie Makers E161563 entity
Predicate collaboratedWith P435 FINISHED
Object Mahesh Babu E164750 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: Mahesh Babu | Statement: [Mythri Movie Makers, collaboratedWith, Mahesh Babu]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Mahesh Babu
Context triple: [Mythri Movie Makers, collaboratedWith, Mahesh Babu]
  • A. Mahesh Babu chosen
    Mahesh Babu is a leading Indian actor and producer best known for his work in Telugu cinema, where he is celebrated for his charismatic screen presence and numerous blockbuster films.
  • B. Pawan Kalyan
    Pawan Kalyan is a prominent Indian film actor, producer, and politician best known for his work in Telugu cinema and his charismatic screen presence.
  • C. Prabhas
    Prabhas is an Indian film actor best known for his leading role in the blockbuster "Baahubali" series, which brought him international fame.
  • D. Ram Charan
    Ram Charan is a prominent Indian film actor and producer best known for his leading roles in Telugu cinema and for being one of the highest-paid actors in the industry.
  • E. Venkatesh Daggubati
    Venkatesh Daggubati is a prominent Indian film actor best known for his work in Telugu cinema, where he has had a successful career spanning several decades.
  • 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_69c68853cff881908439d488924a8283 completed March 27, 2026, 1:38 p.m.
NER Named-entity recognition batch_69c6db152b2081909271493a5d1469fb completed March 27, 2026, 7:31 p.m.
NED1 Entity disambiguation (via context triple) batch_69c7bf709c4c819090c35eb41f46f5d2 completed March 28, 2026, 11:45 a.m.
Created at: March 27, 2026, 2:30 p.m.