Triple

T16133779
Position Surface form Disambiguated ID Type / Status
Subject Girl with a Suitcase E391468 entity
Predicate distributedBy P1951 FINISHED
Object Cineriz E539888 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: Cineriz | Statement: [Girl with a Suitcase, distributedBy, Cineriz]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Cineriz
Context triple: [Girl with a Suitcase, distributedBy, Cineriz]
  • A. Cineriz chosen
    Cineriz was an Italian film production and distribution company known for handling prominent auteur films during the mid-20th century.
  • B. Cyanika
    Cyanika is a town in northern Rwanda that serves as the administrative center of Burera District.
  • C. Cenere
    Cenere is a 1916 Italian silent drama film, notable for starring celebrated actress Eleonora Duse in one of her rare screen appearances.
  • D. Nivala
    Nivala is a small town and municipality in Northern Ostrobothnia, Finland, known for its rural character and agricultural surroundings.
  • E. Sulien
    Sulien is a Welsh saint traditionally venerated as a local holy figure associated with churches in Wales.
  • 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_69d87f1bb0988190b490d273dbf3fd03 completed April 10, 2026, 4:39 a.m.
NER Named-entity recognition batch_69e21a039f0c8190a679e16a27f2dbe3 completed April 17, 2026, 11:31 a.m.
NED1 Entity disambiguation (via context triple) batch_69fff7a304348190bf471f2b9279b806 completed May 10, 2026, 3:12 a.m.
Created at: April 10, 2026, 5:01 a.m.