Triple

T5227783
Position Surface form Disambiguated ID Type / Status
Subject The Robe E118034 entity
Predicate mainCharacter P1183 FINISHED
Object Diana E71669 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: Diana | Statement: [The Robe, mainCharacter, Diana]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Diana
Context triple: [The Robe, mainCharacter, Diana]
  • A. Diana chosen
    Diana is a feminine given name of Latin origin, famously borne by the Roman goddess of the hunt and by Diana, Princess of Wales.
  • B. Melina
    Melina is a key resistance fighter and love interest in the science fiction film "Total Recall," known for aiding the protagonist in his struggle against a corrupt Martian regime.
  • C. Diane
    Diane is a feminine given name of Latin origin, derived from the name of the Roman goddess Diana.
  • D. Isidora
    Isidora is a feminine given name of Greek origin, commonly considered the female form of Isidore and meaning "gift of Isis."
  • E. Anastasia
    Anastasia is a 1956 historical drama film starring Ingrid Bergman as an amnesiac woman who may be the surviving daughter of Russia’s last tsar.
  • 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_69bd4466fb8c819083b806a79414d7e4 completed March 20, 2026, 12:58 p.m.
NER Named-entity recognition batch_69bd7addbdb88190baf9f47fc4cbb7fc completed March 20, 2026, 4:50 p.m.
NED1 Entity disambiguation (via context triple) batch_69beeffea8f481909c86c932781c4e2a completed March 21, 2026, 7:22 p.m.
Created at: March 20, 2026, 1:48 p.m.