Triple

T21109487
Position Surface form Disambiguated ID Type / Status
Subject Mollywood E520135 entity
Predicate hasNotableActor P17435 FINISHED
Object Mohanlal NE NERFINISHED

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: Mohanlal | Statement: [Mollywood, hasNotableActor, Mohanlal]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Mohanlal
Context triple: [Mollywood, hasNotableActor, Mohanlal]
  • A. Mohanlal chosen
    Mohanlal is a highly acclaimed Indian film actor, primarily known for his work in Malayalam cinema, celebrated for his versatile performances and numerous prestigious awards.
  • B. Mohanlal Gautam
    Mohanlal Gautam was an Indian political figure associated with the early socialist movement who played a key role in establishing the Congress Socialist Party.
  • C. Mammootty
    Mammootty is a legendary Indian film actor and Malayalam cinema icon renowned for his versatile performances across hundreds of films and multiple decades.
  • D. Dileep
    Dileep is an Indian film actor and producer best known for his work in Malayalam cinema.
  • E. Prithviraj Sukumaran
    Prithviraj Sukumaran is an acclaimed Indian film actor, producer, and director primarily known for his work in Malayalam cinema, with notable performances across multiple South Indian and Hindi films.
  • F. None of above.
  • G. Unsure - the case is ambiguous/there is not enough information to decide.

Provenance (2 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_69e0b509a318819092fbbcb21d1fe603 completed April 16, 2026, 10:08 a.m.
NER Named-entity recognition batch_69e7210110a48190a6359b6732f6293d completed April 21, 2026, 7:02 a.m.
Created at: April 16, 2026, 2:54 p.m.