Triple

T7644069
Position Surface form Disambiguated ID Type / Status
Subject The Snow Queen E173077 entity
Predicate featuresCharacter P626 FINISHED
Object Gerda E677904 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: Gerda | Statement: [The Snow Queen, featuresCharacter, Gerda]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Gerda
Context triple: [The Snow Queen, featuresCharacter, Gerda]
  • A. Gerda chosen
    Gerda is the brave and devoted young heroine of Hans Christian Andersen’s fairy tale who embarks on a perilous journey to rescue her friend Kai from the Snow Queen.
  • B. Grete
    Grete is the given name of Grete Hermann, a German mathematician and philosopher known for her pioneering work in the foundations of quantum mechanics and computer algebra.
  • C. Astrid
    Astrid is a Belgian princess and member of the country’s royal family.
  • D. Birgitte
    Birgitte is a Danish-born member of the British royal family who holds the title Duchess of Gloucester.
  • E. Ottilia
    Ottilia is a feminine given name of Germanic origin, related to Otto and typically interpreted to mean "wealth" or "prosperity."
  • 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_69c6995360188190968ee57b72a1627f completed March 27, 2026, 2:50 p.m.
NER Named-entity recognition batch_69c6faf13858819095262664e1e04eb7 completed March 27, 2026, 9:47 p.m.
NED1 Entity disambiguation (via context triple) batch_69c89acaac6481908ef763647a0ca9b3 completed March 29, 2026, 3:21 a.m.
Created at: March 27, 2026, 3:58 p.m.