Triple

T23439423
Position Surface form Disambiguated ID Type / Status
Subject Anushka Sharma E565353 entity
Predicate coStarredWith P14987 FINISHED
Object Ranveer Singh NE NERFINISHED

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: Ranveer Singh | Statement: [Anushka Sharma, coStarredWith, Ranveer Singh]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Ranveer Singh
Context triple: [Anushka Sharma, coStarredWith, Ranveer Singh]
  • A. Ranveer Singh chosen
    Ranveer Singh is a popular Indian film actor known for his energetic performances and leading roles in numerous successful Bollywood movies.
  • B. Ranbir Kapoor
    Ranbir Kapoor is a prominent Indian film actor and producer known for his leading roles in contemporary Hindi cinema.
  • C. Ayushmann Khurrana
    Ayushmann Khurrana is an acclaimed Indian actor and singer known for his unconventional film choices and performances in Hindi cinema.
  • D. Ranbir Singh
    Ranbir Singh was a 19th-century Maharaja of Jammu and Kashmir known for consolidating Dogra rule and promoting administrative, legal, and educational reforms in the princely state.
  • E. Rajkummar Rao
    Rajkummar Rao is an acclaimed Indian film actor known for his versatile performances in Hindi cinema, particularly in critically praised independent and mainstream films.
  • F. None of above.
  • G. Unsure - the case is ambiguous/there is not enough information to decide.

Provenance (2 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_69e24584f9488190bb32730bd2ce023e completed April 17, 2026, 2:36 p.m.
NER Named-entity recognition batch_69f1a5de713c8190b35bfa66dddbd5af completed April 29, 2026, 6:31 a.m.
Created at: April 17, 2026, 5:50 p.m.