Triple

T9015557
Position Surface form Disambiguated ID Type / Status
Subject The Fall (2006 film) E215584 entity
Predicate starring P1507 FINISHED
Object Jeetu Verma E471140 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: Jeetu Verma | Statement: [The Fall (2006 film), starring, Jeetu Verma]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Jeetu Verma
Context triple: [The Fall (2006 film), starring, Jeetu Verma]
  • A. Jeetu Verma chosen
    Jeetu Verma is an Indian character actor known for supporting and villainous roles in Hindi films, including a part in the fantasy drama "The Fall" (2006).
  • B. Raghuveer Chaudhari
    Raghuveer Chaudhari is an acclaimed Indian Gujarati writer and scholar renowned for his influential novels, poetry, and literary criticism.
  • C. Ajay Kumar
    Ajay Kumar is an Indian screenwriter best known for contributing dialogue to major Telugu-language films, including the epic blockbuster "Baahubali: The Beginning."
  • D. Mukul Sharma
    Mukul Sharma was an Indian writer, journalist, and science fiction author known for his popular science columns and for inspiring several acclaimed film adaptations.
  • E. Vijay Kumar
    Vijay Kumar is a prominent roboticist and engineer known for his pioneering work in multi-robot systems and aerial robotics.
  • 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_69ca83a38aa88190bf1bb80c4548b5e2 completed March 30, 2026, 2:07 p.m.
NER Named-entity recognition batch_69cc69fc0e4c819080b60456375f94cd completed April 1, 2026, 12:42 a.m.
NED1 Entity disambiguation (via context triple) batch_69cfdba8bd8c81909860d561d9d16611 completed April 3, 2026, 3:24 p.m.
Created at: March 30, 2026, 7:06 p.m.