Triple

T11289302
Position Surface form Disambiguated ID Type / Status
Subject Shashi Kapoor E267281 entity
Predicate employer P7 FINISHED
Object Prithvi Theatres E904726 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: Prithvi Theatres | Statement: [Shashi Kapoor, employer, Prithvi Theatres]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Prithvi Theatres
Context triple: [Shashi Kapoor, employer, Prithvi Theatres]
  • A. Prithvi Theatres chosen
    Prithvi Theatres was a pioneering Indian theatre company established in the mid-20th century that played a major role in popularizing Hindi theatre across India.
  • B. Shiva Theater
    Shiva Theater is one of the performance spaces within New York City's Public Theater complex, used for staging a variety of theatrical productions.
  • C. Regal Theatre
    Regal Theatre was a historic Chicago entertainment venue renowned for showcasing African American performers during the early to mid-20th century.
  • D. Olympion Cinema
    Olympion Cinema is a historic movie theater and cultural landmark in Thessaloniki, Greece, best known for hosting the city’s prestigious international film festival.
  • E. Cinema City
    Cinema City is a European cinema chain brand operated by Cineworld Group, known for its multiplex movie theaters across several countries.
  • 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_69d6aac993a08190a6f36445ebaf9a43 completed April 8, 2026, 7:21 p.m.
NER Named-entity recognition batch_69d7e98875a08190b8509fe55e49d52d completed April 9, 2026, 6:01 p.m.
NED1 Entity disambiguation (via context triple) batch_69e4f48e190c8190b46d4286e2acaef1 completed April 19, 2026, 3:28 p.m.
Created at: April 8, 2026, 9:32 p.m.