Triple

T6969667
Position Surface form Disambiguated ID Type / Status
Subject SIIMA Awards E161569 entity
Predicate awardCategoryType P1498 FINISHED
Object Best Actress E11087 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: Best Actress | Statement: [SIIMA Awards, awardCategoryType, Best Actress]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Best Actress
Context triple: [SIIMA Awards, awardCategoryType, Best Actress]
  • A. Best Actress chosen
    Best Actress is a major Academy Award category that honors the most outstanding leading performance by a female actor in a given year.
  • B. Best Actress Award
    The Best Actress Award is a top acting honor presented at the Thessaloniki International Film Festival to recognize the most outstanding female performance in a film showcased at the event.
  • C. Best Actor
    Best Actor is a prestigious Academy Award category honoring the most outstanding leading performance by a male actor in a given film year.
  • D. Best Actor
    Best Actor is a leading performance award category recognizing outstanding male acting in television at the International Emmy Awards Gala.
  • E. Golden Calf for Best Actress
    The Golden Calf for Best Actress is a premier Dutch film award honoring the year’s most outstanding leading female performance in cinema.
  • 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_69c68853cff881908439d488924a8283 completed March 27, 2026, 1:38 p.m.
NER Named-entity recognition batch_69c6db1649288190a52c7dab57b3c7dc completed March 27, 2026, 7:31 p.m.
NED1 Entity disambiguation (via context triple) batch_69c7619ebab88190916e3d68068ed71d completed March 28, 2026, 5:05 a.m.
Created at: March 27, 2026, 2:30 p.m.