Triple

T8564886
Position Surface form Disambiguated ID Type / Status
Subject Suriya E202778 entity
Predicate notableWork P4 FINISHED
Object Pithamagan E741423 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: Pithamagan | Statement: [Suriya, notableWork, Pithamagan]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Pithamagan
Context triple: [Suriya, notableWork, Pithamagan]
  • A. Pithamagan chosen
    Pithamagan is a 2003 Tamil-language drama film directed by Bala, acclaimed for Vikram’s intense performance as a socially isolated graveyard worker.
  • B. Pitadeniya
    Pitadeniya is a village and gateway area in southern Sri Lanka that serves as a main entry point for visitors to the Sinharaja Forest Reserve.
  • C. Pamankada
    Pamankada is a residential and commercial neighborhood within the city of Colombo, Sri Lanka.
  • D. The Ganachery
    The Ganachery is an artisanal chocolate shop at Disney Springs known for its handcrafted ganache and specialty confections.
  • E. Badagu Thittu
    Badagu Thittu is a major northern style of the traditional South Indian dance-drama Yakshagana, known for its elaborate costumes, vigorous dance, and distinctive musical patterns.
  • 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_69ca8327b0a881908606ff860713964d completed March 30, 2026, 2:05 p.m.
NER Named-entity recognition batch_69cbe9d11274819099cc33a21a993a1f completed March 31, 2026, 3:35 p.m.
NED1 Entity disambiguation (via context triple) batch_69ce89677888819091dfda14ce6baef3 completed April 2, 2026, 3:21 p.m.
Created at: March 30, 2026, 6:20 p.m.