Triple

T8558340
Position Surface form Disambiguated ID Type / Status
Subject Nayanthara E202631 entity
Predicate activeIn P1560 FINISHED
Object Malayalam cinema E520135 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: Malayalam cinema | Statement: [Nayanthara, activeIn, Malayalam cinema]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Malayalam cinema
Context triple: [Nayanthara, activeIn, Malayalam cinema]
  • A. Mollywood (Malayalam cinema) chosen
    Mollywood (Malayalam cinema) is the Malayalam-language film industry based in the Indian state of Kerala, renowned for its realistic storytelling, strong scripts, and critically acclaimed performances.
  • B. Tamil cinema
    Tamil cinema is the film industry based in the Indian state of Tamil Nadu, primarily producing Tamil-language movies and known for its influential contributions to Indian and global cinema.
  • 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. Kannada cinema
    Kannada cinema is the segment of Indian film industry that produces movies in the Kannada language, primarily based in the state of Karnataka.
  • E. Pollywood
    Pollywood is the regional film industry based in the Indian state of Punjab, producing Punjabi-language movies and entertainment content.
  • 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_69ca8326e6c881908ff720d6abaebdc5 completed March 30, 2026, 2:05 p.m.
NER Named-entity recognition batch_69cbe9485dd88190bc2cf2adf39d48ee completed March 31, 2026, 3:33 p.m.
NED1 Entity disambiguation (via context triple) batch_69ce89455dcc819088bdf5a2f653da17 completed April 2, 2026, 3:20 p.m.
Created at: March 30, 2026, 6:20 p.m.