Triple

T14089208
Position Surface form Disambiguated ID Type / Status
Subject Isabella of Burgundy E339077 entity
Predicate givenName P17 FINISHED
Object Isabella E569457 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: Isabella | Statement: [Isabella of Burgundy, givenName, Isabella]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Isabella
Context triple: [Isabella of Burgundy, givenName, Isabella]
  • A. 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.
  • B. Isabella
    Isabella was a Spanish Habsburg archduchess who governed the Spanish Netherlands in the late 16th and early 17th centuries.
  • C. Isabella
    Isabella was a 15th-century Aragonese princess who became Queen of Portugal through her marriage to King Manuel I.
  • D. Isabella chosen
    Isabella is a feminine given name of Spanish and Italian origin, derived from Elizabeth and widely used across many cultures.
  • E. Isabella
    Isabella is the given name of Lady Gregory, the influential Irish dramatist, folklorist, and co-founder of Dublin’s Abbey Theatre.
  • 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_69d81c687b0c819087fd9ed4198403f8 completed April 9, 2026, 9:38 p.m.
NER Named-entity recognition batch_69de5ee1ce88819091c983286289337e completed April 14, 2026, 3:36 p.m.
NED1 Entity disambiguation (via context triple) batch_69fcd0a5c9948190805c2e687c8809ff completed May 7, 2026, 5:49 p.m.
Created at: April 9, 2026, 10:21 p.m.