Triple

T21739478
Position Surface form Disambiguated ID Type / Status
Subject Elly E536614 entity
Predicate meaningDerivedFrom P14723 FINISHED
Object Elisabeth NE NERFINISHED

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: Elisabeth | Statement: [Elly, meaningDerivedFrom, Elisabeth]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Elisabeth
Context triple: [Elly, meaningDerivedFrom, Elisabeth]
  • A. Elisabeth chosen
    Elisabeth is a feminine given name of Hebrew origin, commonly used in various European languages as a form of Elizabeth.
  • B. Elisabeth
    Elisabeth is a metro station on the Brussels Metro system in Brussels, Belgium.
  • C. Louise of Great Britain
    Louise of Great Britain was a British princess who became Queen of Denmark and Norway through her marriage to King Frederick V.
  • D. Elisabeth Albertine
    Elisabeth Albertine was a German princess of the House of Saxe-Hildburghausen who became Duchess consort of Mecklenburg-Strelitz and the mother of Queen Charlotte of the United Kingdom.
  • E. Victoria Adelaide Mary Louisa
    Victoria Adelaide Mary Louisa, better known as Victoria, Princess Royal, was the eldest child of Queen Victoria and Prince Albert and later became German Empress and Queen of Prussia as the wife of Emperor Frederick III.
  • F. None of above.
  • G. Unsure - the case is ambiguous/there is not enough information to decide.

Provenance (2 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_69e0c46df5448190b4322127ffc4c690 completed April 16, 2026, 11:13 a.m.
NER Named-entity recognition batch_69f01a714c208190b96efe23ed3bf0db completed April 28, 2026, 2:24 a.m.
Created at: April 16, 2026, 6:49 p.m.