Triple

T5075275
Position Surface form Disambiguated ID Type / Status
Subject Isabel E114378 entity
Predicate hasAlternativeSpelling P457 FINISHED
Object Ysabel E496543 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: Ysabel | Statement: [Isabel, hasAlternativeSpelling, Ysabel]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Ysabel
Context triple: [Isabel, hasAlternativeSpelling, Ysabel]
  • A. Isidora
    Isidora is a feminine given name of Greek origin, commonly considered the female form of Isidore and meaning "gift of Isis."
  • B. Izabel chosen
    Izabel is a feminine given name, commonly used in various cultures as a variant of Isabel or Isabella.
  • C. Isabella
    Isabella is a virtuous and resourceful young noblewoman in Horace Walpole’s Gothic novel "The Castle of Otranto," whose peril and resistance drive much of the story’s suspense and drama.
  • D. Isabella
    Isabella was a Spanish Habsburg archduchess who governed the Spanish Netherlands in the late 16th and early 17th centuries.
  • E. Isabella
    Isabella was an English princess of the 13th century, daughter of King John of England, who became Lady de Coucy through marriage into the French nobility.
  • 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_69bd443cf28c8190ad371d603563dbdd completed March 20, 2026, 12:57 p.m.
NER Named-entity recognition batch_69bd74d2243481908c1ae62f7123c4e9 completed March 20, 2026, 4:24 p.m.
NED1 Entity disambiguation (via context triple) batch_69becfb9bcf48190acac2714c25de725 completed March 21, 2026, 5:04 p.m.
Created at: March 20, 2026, 1:39 p.m.