Triple

T8558349
Position Surface form Disambiguated ID Type / Status
Subject Nayanthara E202631 entity
Predicate notableCollaboration P8554 FINISHED
Object Vijay E202777 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: Vijay | Statement: [Nayanthara, notableCollaboration, Vijay]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Vijay
Context triple: [Nayanthara, notableCollaboration, Vijay]
  • A. Vijay chosen
    Vijay is a leading Indian film actor and playback singer, predominantly known for his work in Tamil cinema and his massive fan following across South India.
  • B. Prithviraj Kapoor
    Prithviraj Kapoor was a pioneering Indian actor and theatre legend, regarded as one of the founding figures of Hindi cinema and the Kapoor film dynasty.
  • C. Akshay Kumar
    Akshay Kumar is a prominent Indian film actor and producer, known for his action and comedy roles in Bollywood and his long-running, commercially successful career.
  • D. Ajith Kumar
    Ajith Kumar is a prominent Indian film actor and racing driver best known for his leading roles in Tamil cinema and his massive fan following.
  • E. Ajay Devgn
    Ajay Devgn is a prominent Indian film actor, director, and producer known for his intense performances in Hindi cinema and his versatility across action, drama, and comedy roles.
  • 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_69ca8326e6c881908ff720d6abaebdc5 completed March 30, 2026, 2:05 p.m.
NER Named-entity recognition batch_69cbe9485dd88190bc2cf2adf39d48ee completed March 31, 2026, 3:33 p.m.
NED1 Entity disambiguation (via context triple) batch_69cea871dd3081908e24c4d1c60a8381 completed April 2, 2026, 5:33 p.m.
Created at: March 30, 2026, 6:20 p.m.