Triple

T13058369
Position Surface form Disambiguated ID Type / Status
Subject Isie Krige E327637 entity
Predicate givenName P17 FINISHED
Object Isabella
Isabella is a feminine given name of Spanish and Italian origin, widely used across many cultures and often associated with historical queens and literary characters.
 E569457 NE FINISHED

How this triple was built (4 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: [Isie Krige, givenName, Isabella]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07 
Target entity: Isabella
Context triple: [Isie Krige, 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 is the given name of Lady Gregory, the influential Irish dramatist, folklorist, and co-founder of Dublin’s Abbey Theatre.
  • D. Isabella
    Isabella was a medieval European queen consort, notably Isabella of France who became Queen of England as the wife of Edward II and played a key role in his overthrow.
  • E. Isabella
    Isabella was a 15th-century Aragonese princess who became Queen of Portugal through her marriage to King Manuel I.
  • F. None of above. chosen
  • G. Unsure - the case is ambiguous/there is not enough information to decide.
NEDg Description generation gpt-5.1
Instruction
Generate a one-sentence description of the target entity. 
You are given a context triple in the form (subject, predicate, object), where the object is the target entity. 
# Instructions
Use the triple to infer relevant information about the entity. Describe the entity based on what is most defining, well-known. 
Avoid repeating the information from the triple, unless really essential.
# Response Format
Return only the sentence: "Description: [one-sentence description of the target entity]"
Input
Entity: Isabella
Triple: [Isie Krige, givenName, Isabella]
Generated description
Isabella is a feminine given name of Spanish and Italian origin, widely used across many cultures and often associated with historical queens and literary characters.
NED2 Entity disambiguation (via description) gpt-5-mini-2025-08-07 
Target entity: Isabella
Target entity description: Isabella is a feminine given name of Spanish and Italian origin, widely used across many cultures and often associated with historical queens and literary characters.
  • A. Isabella chosen
    Isabella is a feminine given name of Spanish and Italian origin, derived from Elizabeth and widely used across many cultures.
  • B. Isabella
    Isabella is the given name of Lady Gregory, the influential Irish dramatist, folklorist, and co-founder of Dublin’s Abbey Theatre.
  • C. Isabella
    Isabella was a Spanish Habsburg archduchess who governed the Spanish Netherlands in the late 16th and early 17th centuries.
  • D. Isabella
    Isabella was a medieval European queen consort, notably Isabella of France who became Queen of England as the wife of Edward II and played a key role in his overthrow.
  • E. Isabella
    Isabella was a 15th-century Aragonese princess who became Queen of Portugal through her marriage to King Manuel I.
  • F. None of above.

Provenance (5 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_69d8076e64308190904fb5c93517c901 completed April 9, 2026, 8:09 p.m.
NER Named-entity recognition batch_69d980be37208190962e91f1e19df159 completed April 10, 2026, 10:59 p.m.
NED1 Entity disambiguation (via context triple) batch_69f6d5ff8c308190a40274c68a1c5da3 completed May 3, 2026, 4:58 a.m.
NEDg Description generation batch_69f6d8c8a8b48190a2dc2f6b5e7d37e0 completed May 3, 2026, 5:10 a.m.
NED2 Entity disambiguation (via description) batch_69f6d98d6ba48190b63f6330ba215c36 completed May 3, 2026, 5:13 a.m.
Created at: April 9, 2026, 8:58 p.m.