Triple

T9616974
Position Surface form Disambiguated ID Type / Status
Subject Snowgies E232242 entity
Predicate associatedWithCharacter P1481 FINISHED
Object Anna
Anna is a central character from Disney's Frozen franchise, known as the optimistic and fearless princess (later queen) of Arendelle and Elsa's younger sister.
 E198466 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: [Snowgies, associatedWithCharacter, Anna]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07 
Target entity: Anna
Context triple: [Snowgies, associatedWithCharacter, Anna]
  • A. Anna
    Anna is the given first name of Eleanor Roosevelt, the influential former First Lady of the United States and human rights advocate.
  • B. Anna
    Anna is the given name of Anna Murray Douglass, an African American abolitionist and the first wife of Frederick Douglass.
  • C. 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.
  • D. Anna
    Anna is the given name of Anna Laetitia Barbauld, an influential 18th–19th century English poet, essayist, and children's author.
  • E. Anna
    Anna is traditionally revered in Christianity as the mother of the Virgin Mary and the grandmother of Jesus.
  • 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: [Snowgies, associatedWithCharacter, Anna]
Generated description
Anna is a central character from Disney's Frozen franchise, known as the optimistic and fearless princess (later queen) of Arendelle and Elsa's younger sister.
NED2 Entity disambiguation (via description) gpt-5-mini-2025-08-07 
Target entity: Anna
Target entity description: Anna is a central character from Disney's Frozen franchise, known as the optimistic and fearless princess (later queen) of Arendelle and Elsa's younger sister.
  • A. Anna chosen
    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.
  • B. Anna
    Anna is a character from the "Predator" franchise, appearing as one of the human figures caught up in the deadly encounters with the extraterrestrial hunter.
  • C. Anna
    Anna is a character appearing in the home-renovation reality TV series "Fixer Upper."
  • D. Anna
    Anna is the tragic, aristocratic heroine of Leo Tolstoy’s novel "Anna Karenina," whose passionate affair and struggle against societal norms lead to her downfall.
  • E. 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.
  • 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_69ca84867bb88190b4b57dd5a56d5691 completed March 30, 2026, 2:11 p.m.
NER Named-entity recognition batch_69cd9aaf3a088190a00a7750c25b6c42 completed April 1, 2026, 10:22 p.m.
NED1 Entity disambiguation (via context triple) batch_69d189f4e994819088c55856bf79621d completed April 4, 2026, 10 p.m.
NEDg Description generation batch_69d18acf86588190bc000f701bcaaa1c completed April 4, 2026, 10:03 p.m.
NED2 Entity disambiguation (via description) batch_69d18ba396cc8190a3ded2ac3968c553 completed April 4, 2026, 10:07 p.m.
Created at: March 30, 2026, 8:09 p.m.