Triple

T170987
Position Surface form Disambiguated ID Type / Status
Subject Judy Garland E3121 entity
Predicate givenName P17 FINISHED
Object Frances E12143 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: Frances | Statement: [Judy Garland, givenName, Frances]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Frances
Context triple: [Judy Garland, givenName, Frances]
  • A. Frances chosen
    Frances is a feminine given name of Latin origin, commonly used in English-speaking countries.
  • B. Natal
    Natal is a historical region in southeastern South Africa, centered on the port city of Durban and known for its colonial history and diverse cultural heritage.
  • C. Douglas
    Douglas is a masculine given name of Scottish origin that has been widely used in English-speaking countries.
  • D. Valais
    Valais is a mountainous canton in southwestern Switzerland known for its Alpine scenery, vineyards, and popular ski resorts such as Zermatt and Verbier.
  • E. Heart of America
    Heart of America is a nickname for Kansas City, Missouri, highlighting its central location and cultural significance in the United States.
  • 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_69a2524ce1e48190ab066bf72859f474 completed Feb. 28, 2026, 2:26 a.m.
NER Named-entity recognition batch_69a258b94d00819098e90bdfa1306f9f completed Feb. 28, 2026, 2:53 a.m.
NED1 Entity disambiguation (via context triple) batch_69a2ee8962a88190b6821e55f435c8b7 completed Feb. 28, 2026, 1:32 p.m.
Created at: Feb. 28, 2026, 2:34 a.m.