Triple

T11102870
Position Surface form Disambiguated ID Type / Status
Subject Boney Kapoor E262553 entity
Predicate notableCollaboration P8554 FINISHED
Object Ajith Kumar E205711 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: Ajith Kumar | Statement: [Boney Kapoor, notableCollaboration, Ajith Kumar]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Ajith Kumar
Context triple: [Boney Kapoor, notableCollaboration, Ajith Kumar]
  • A. Ajith Kumar chosen
    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.
  • B. Mahesh Babu
    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.
  • C. Vijay
    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.
  • D. Vijay Sethupathi
    Vijay Sethupathi is a critically acclaimed Indian actor, primarily known for his versatile performances in Tamil cinema across a wide range of complex and unconventional roles.
  • E. Dileep
    Dileep is an Indian film actor and producer best known for his work in Malayalam cinema.
  • 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_69d6aa9a40d88190a373e2c7e48285db completed April 8, 2026, 7:20 p.m.
NER Named-entity recognition batch_69d79a2c30a481908c45020c37caebe4 completed April 9, 2026, 12:23 p.m.
NED1 Entity disambiguation (via context triple) batch_69e3e7ff368c8190ab01b7538ad83826 completed April 18, 2026, 8:22 p.m.
Created at: April 8, 2026, 9:27 p.m.