Triple

T14711230
Position Surface form Disambiguated ID Type / Status
Subject Bella Swan E345551 entity
Predicate givenName P17 FINISHED
Object Isabella
Isabella is the full first name of Bella Swan, the main human protagonist of the Twilight series.
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: [Bella Swan, givenName, Isabella]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Isabella
Context triple: [Bella Swan, 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 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 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.
  • D. Isabella
    Isabella was a Polish princess of the Jagiellonian dynasty who became Queen consort of Hungary in the 16th century.
  • E. Isabella
    Isabella of Burgundy was a 15th-century duchess consort of Burgundy, known for her political influence and role in the Burgundian court during the late Middle Ages.
  • 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: [Bella Swan, givenName, Isabella]
Generated description
Isabella is the full first name of Bella Swan, the main human protagonist of the Twilight series.
NED2 Entity disambiguation (via description) gpt-5-mini-2025-08-07
Target entity: Isabella
Target entity description: Isabella is the full first name of Bella Swan, the main human protagonist of the Twilight series.
  • 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 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.
  • C. Isabella
    Isabella is the tragic heroine of John Keats’s narrative poem “Isabella; or, The Pot of Basil,” known for her doomed love and macabre devotion to her murdered lover.
  • D. Isabella
    Isabella is the given name of Mrs Beeton, the famed 19th-century English author of the influential household management guide "Mrs Beeton's Book of Household Management."
  • 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.

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_69d822e4a8c08190a155df736bb7bc13 completed April 9, 2026, 10:06 p.m.
NER Named-entity recognition batch_69deb9814e0c8190984ac30d276499cc completed April 14, 2026, 10:02 p.m.
NED1 Entity disambiguation (via context triple) batch_69fdfb7c7df88190a4e551a12f6e8158 completed May 8, 2026, 3:04 p.m.
NEDg Description generation batch_69fe08c5131881908d29c8dfc6c0b7cd completed May 8, 2026, 4:01 p.m.
NED2 Entity disambiguation (via description) batch_69fe093c3cf88190bff00387f7516295 completed May 8, 2026, 4:03 p.m.
Created at: April 10, 2026, 1:28 a.m.