Triple

T5752683
Position Surface form Disambiguated ID Type / Status
Subject Little Women (2019 film) E126888 entity
Predicate productionCompany P490 FINISHED
Object Pascal Pictures E226121 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: Pascal Pictures | Statement: [Little Women (2019 film), productionCompany, Pascal Pictures]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Pascal Pictures
Context triple: [Little Women (2019 film), productionCompany, Pascal Pictures]
  • A. Pascal Pictures chosen
    Pascal Pictures is a film and television production company founded by producer Amy Pascal, known for backing high-profile, critically acclaimed projects.
  • B. Component Pascal
    Component Pascal is a modern, strongly typed programming language in the Oberon family, designed for component-based software development with an emphasis on safety and simplicity.
  • C. Pascal
    Pascal is the small, expressive chameleon who serves as Rapunzel’s loyal companion and confidant in Disney’s animated film "Tangled."
  • D. Pascal
    Pascal is a French surname most famously associated with Blaise Pascal, the 17th-century mathematician, physicist, inventor, and philosopher.
  • E. Pascal
    Pascal is a high-level, strongly typed procedural programming language designed by Niklaus Wirth in the late 1960s, widely used for teaching structured programming and data structuring concepts.
  • 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_69c00832aedc81909899801b141fa3b4 completed March 22, 2026, 3:18 p.m.
NER Named-entity recognition batch_69c0288b580c81909e1289982b106695 completed March 22, 2026, 5:36 p.m.
NED1 Entity disambiguation (via context triple) batch_69c07e3e71988190a938a6d175023028 completed March 22, 2026, 11:41 p.m.
Created at: March 22, 2026, 3:48 p.m.