Triple

T7073282
Position Surface form Disambiguated ID Type / Status
Subject Dil Raju E164751 entity
Predicate industry P71 FINISHED
Object Tollywood E31774 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: Tollywood | Statement: [Dil Raju, industry, Tollywood]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Tollywood
Context triple: [Dil Raju, industry, Tollywood]
  • A. Tollywood
    Tollywood is the Bengali-language film industry based primarily in Kolkata, India, known for its rich artistic and literary cinematic tradition.
  • B. Pollywood
    Pollywood is the regional film industry based in the Indian state of Punjab, producing Punjabi-language movies and entertainment content.
  • C. Mollywood
    Mollywood is the Malayalam-language film industry based in the Indian state of Kerala, known for its content-driven cinema and strong storytelling traditions.
  • D. Kollywood
    Kollywood is the Tamil-language film industry based in Chennai, India, known for its prolific output of commercial and artistic cinema.
  • E. Tollywood film industry chosen
    The Tollywood film industry is the segment of Indian cinema that produces movies in the Telugu language, primarily based in Hyderabad.
  • 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_69c6887b96548190a8a9b3ac8adf4119 completed March 27, 2026, 1:39 p.m.
NER Named-entity recognition batch_69c6e4cb76548190bd98876f8ba925b7 completed March 27, 2026, 8:12 p.m.
NED1 Entity disambiguation (via context triple) batch_69c84eda551081909c8489f3848846f3 completed March 28, 2026, 9:57 p.m.
Created at: March 27, 2026, 2:39 p.m.