Triple

T5688003
Position Surface form Disambiguated ID Type / Status
Subject Lollywood E125358 entity
Predicate developedFrom P1245 FINISHED
Object Lahore film industry E125358 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: Lahore film industry | Statement: [Lollywood, developedFrom, Lahore film industry]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Lahore film industry
Context triple: [Lollywood, developedFrom, Lahore film industry]
  • A. Pakistani cinema
    Pakistani cinema is the film industry of Pakistan, encompassing movies produced in various regional languages and known for its evolving storytelling, music, and cultural influence across South Asia.
  • B. Punjabi cinema
    Punjabi cinema is the film industry that produces motion pictures in the Punjabi language, primarily based in the Punjab regions of India and Pakistan.
  • C. Balochi cinema
    Balochi cinema is the regional film industry that produces movies in the Balochi language, reflecting the culture and stories of the Baloch people within Pakistan and neighboring regions.
  • D. Lollywood chosen
    Lollywood is the Pakistani film industry based in Lahore, historically known for producing Punjabi- and Urdu-language movies.
  • E. Pashto cinema
    Pashto cinema is the film industry producing movies in the Pashto language, primarily based in Pakistan’s Khyber Pakhtunkhwa region and catering to Pashto-speaking audiences.
  • 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_69c0082a884c8190a79001bae658941f completed March 22, 2026, 3:18 p.m.
NER Named-entity recognition batch_69c023be18a081908c72fb5b0e1852f9 completed March 22, 2026, 5:15 p.m.
NED1 Entity disambiguation (via context triple) batch_69c05a43cce88190b8ac801018f05561 completed March 22, 2026, 9:08 p.m.
Created at: March 22, 2026, 3:44 p.m.