Triple

T5226071
Position Surface form Disambiguated ID Type / Status
Subject Anne Bancroft E117990 entity
Predicate givenName P17 FINISHED
Object Anna
Anna is the given name of Anne Bancroft, the acclaimed American actress best known for her role as Mrs. Robinson in "The Graduate."
 E505776 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: [Anne Bancroft, givenName, Anna]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07 
Target entity: Anna
Context triple: [Anne Bancroft, 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: [Anne Bancroft, givenName, Anna]
Generated description
Anna is the given name of Anne Bancroft, the acclaimed American actress best known for her role as Mrs. Robinson in "The Graduate."
NED2 Entity disambiguation (via description) gpt-5-mini-2025-08-07 
Target entity: Anna
Target entity description: Anna is the given name of Anne Bancroft, the acclaimed American actress best known for her role as Mrs. Robinson in "The Graduate."
  • 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 pioneering Chinese American actress Anna May Wong, a trailblazing early Hollywood star and fashion icon.
  • C. Anna
    Anna is the given name of Anna Murray Douglass, an African American abolitionist and the first wife of Frederick Douglass.
  • 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 an actress known for portraying the ambitious and manipulative Lady Macbeth in a production of Shakespeare’s tragedy "Macbeth."
  • 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_69bd4466fb8c819083b806a79414d7e4 completed March 20, 2026, 12:58 p.m.
NER Named-entity recognition batch_69bd7adc9be081909903b9f844c3d146 completed March 20, 2026, 4:50 p.m.
NED1 Entity disambiguation (via context triple) batch_69bef809189c8190b61bd386480c0222 completed March 21, 2026, 7:56 p.m.
NEDg Description generation batch_69befbe661208190af7c9490a386a9e5 completed March 21, 2026, 8:13 p.m.
NED2 Entity disambiguation (via description) batch_69befc4605008190882c00cac6362a8d completed March 21, 2026, 8:15 p.m.
Created at: March 20, 2026, 1:48 p.m.