Triple

T14891477
Position Surface form Disambiguated ID Type / Status
Subject Joy Davidman E359762 entity
Predicate notableWork P4 FINISHED
Object Anya E563376 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: Anya | Statement: [Joy Davidman, notableWork, Anya]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Anya
Context triple: [Joy Davidman, notableWork, Anya]
  • A. Anya
    Anya is a person known primarily through her relationship to someone named Hannah, likely as a friend or family member.
  • B. Anya
    Anya is the given name of actress Anya Taylor-Joy, known for her roles in films like "The Witch" and the series "The Queen's Gambit."
  • C. Anya chosen
    Anya is the spirited, amnesiac young woman in the animated film "Anastasia" who embarks on a journey to discover whether she is the lost Russian Grand Duchess.
  • D. Anya Taranda
    Anya Taranda was an American fashion model and actress best known for her work in the 1930s and 1940s.
  • E. Anya Amasova
    Anya Amasova is a Soviet KGB agent and Bond girl featured in the James Bond film "The Spy Who Loved Me."
  • 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_69d827980cbc8190a0c569ae3940a1d9 completed April 9, 2026, 10:26 p.m.
NER Named-entity recognition batch_69ded5f883288190af602633fa7d6860 completed April 15, 2026, 12:04 a.m.
NED1 Entity disambiguation (via context triple) batch_69fe6b65ac5c81908691de1161d07de0 completed May 8, 2026, 11:01 p.m.
Created at: April 10, 2026, 2:10 a.m.