Triple

T4804930
Position Surface form Disambiguated ID Type / Status
Subject Anna Netrebko E106924 entity
Predicate givenName P17 FINISHED
Object Anna
Anna is a feminine given name widely used across many cultures, particularly in Europe and the Americas, often associated with historical, religious, and literary figures.
 E161036 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: Anna | Statement: [Anna Netrebko, givenName, Anna]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07 
Target entity: Anna
Context triple: [Anna Netrebko, givenName, Anna]
  • A. Anna
    Anna is the given name of Anna Murray Douglass, an African American abolitionist and the first wife of Frederick Douglass.
  • B. Anna
    Anna is a central female character in the comedy Western film "A Million Ways to Die in the West," portrayed as a sharp-shooting, quick-witted woman who helps the protagonist toughen up in the dangerous frontier.
  • C. Anna
    Anna is the given name of pioneering Chinese American actress Anna May Wong, a trailblazing early Hollywood star and fashion icon.
  • D. Anna
    Anna is a character from the video game "Surfacing," likely serving as a key figure in the game's narrative or player interactions.
  • E. Anna
    Anna is a spirited and optimistic princess from Disney's animated film "Frozen," known for her bravery, loyalty, and deep love for her sister Elsa.
  • 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: Anna
Triple: [Anna Netrebko, givenName, Anna]
Generated description
Anna is a feminine given name widely used across many cultures, particularly in Europe and the Americas, often associated with historical, religious, and literary figures.
NED2 Entity disambiguation (via description) gpt-5-mini-2025-08-07 
Target entity: Anna
Target entity description: Anna is a feminine given name widely used across many cultures, particularly in Europe and the Americas, often associated with historical, religious, and literary figures.
  • A. Anna chosen
    Anna is a feminine given name of Hebrew origin meaning "grace" or "favor," widely used across many cultures and languages.
  • B. Anna
    Anna is the given first name of Eleanor Roosevelt, the influential former First Lady of the United States and human rights advocate.
  • C. Anna
    Anna is the given name of Anna Laetitia Barbauld, an influential 18th–19th century English poet, essayist, and children's author.
  • D. Anna
    Anna is traditionally revered in Christianity as the mother of the Virgin Mary and the grandmother of Jesus.
  • E. Anna
    Anna is the given name of pioneering Chinese American actress Anna May Wong, a trailblazing early Hollywood star and fashion icon.
  • 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_69bd43f6a1e08190bf0a372bfc336ee5 completed March 20, 2026, 12:56 p.m.
NER Named-entity recognition batch_69bd6c664c3c81908e4d9a7c8c19744b completed March 20, 2026, 3:48 p.m.
NED1 Entity disambiguation (via context triple) batch_69be4403ef888190b41c9a0db6bf47aa completed March 21, 2026, 7:08 a.m.
NEDg Description generation batch_69be44df4e808190bb65ea205446a98f completed March 21, 2026, 7:12 a.m.
NED2 Entity disambiguation (via description) batch_69be45bc7b2c8190aa293d2c10077864 completed March 21, 2026, 7:16 a.m.
Created at: March 20, 2026, 1:23 p.m.