Triple

T8626333
Position Surface form Disambiguated ID Type / Status
Subject Anna Karina E204288 entity
Predicate givenName P17 FINISHED
Object Hanne
Hanne is the birth name of Anna Karina, the acclaimed Danish-French actress and muse of the French New Wave cinema.
E747616 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: Hanne | Statement: [Anna Karina, givenName, Hanne]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Hanne
Context triple: [Anna Karina, givenName, Hanne]
  • A. Hanne
    Hanne is a soprano soloist role representing a young country girl in Joseph Haydn’s oratorio "The Seasons."
  • B. Maddalene
    Maddalene is a feminine given name, typically considered a variant of Maddalena or Magdalene, with roots in Christian and European naming traditions.
  • C. Birgitte
    Birgitte is a Danish-born member of the British royal family who holds the title Duchess of Gloucester.
  • D. Hannah
    Hannah is a biblical figure in the Book of 1 Samuel known for her fervent prayer for a child and as the mother of the prophet Samuel.
  • E. Hannah
    Hannah is a person associated in some way with the city of Santa Ana, California.
  • 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: Hanne
Triple: [Anna Karina, givenName, Hanne]
Generated description
Hanne is the birth name of Anna Karina, the acclaimed Danish-French actress and muse of the French New Wave cinema.
NED2 Entity disambiguation (via description) gpt-5-mini-2025-08-07
Target entity: Hanne
Target entity description: Hanne is the birth name of Anna Karina, the acclaimed Danish-French actress and muse of the French New Wave cinema.
  • A. Hanne
    Hanne is a soprano soloist role representing a young country girl in Joseph Haydn’s oratorio "The Seasons."
  • B. Maddalene
    Maddalene is a feminine given name, typically considered a variant of Maddalena or Magdalene, with roots in Christian and European naming traditions.
  • C. Birgitte
    Birgitte is a Danish-born member of the British royal family who holds the title Duchess of Gloucester.
  • D. Hannah
    Hannah is a compassionate Jewish laundress and the love interest of the Jewish Barber in Charlie Chaplin’s 1940 satirical film "The Great Dictator."
  • E. Hannah
    Hannah is a key survivor character in the British post-apocalyptic horror film "28 Days Later," known for her resilience and resourcefulness amid a rage virus outbreak in London.
  • F. None of above. chosen

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_69ca834a4ea0819094970dceb9e389f3 completed March 30, 2026, 2:06 p.m.
NER Named-entity recognition batch_69cc472b8fa481909f52f83ea210483e completed March 31, 2026, 10:14 p.m.
NED1 Entity disambiguation (via context triple) batch_69cebbf03c688190a989f16675f6e8a6 completed April 2, 2026, 6:56 p.m.
NEDg Description generation batch_69cebdd3ae908190bc4108b766585cbc completed April 2, 2026, 7:04 p.m.
NED2 Entity disambiguation (via description) batch_69cebf1825008190a97cd2df10f8e406 completed April 2, 2026, 7:10 p.m.
Created at: March 30, 2026, 6:26 p.m.