Triple

T16249328
Position Surface form Disambiguated ID Type / Status
Subject Anny Ondra E394457 entity
Predicate givenName P17 FINISHED
Object Anna
Anna is the given first name of Anny Ondra, the Czech-Austrian film actress best known for her work in early European cinema and Alfred Hitchcock’s films.
 E1202337 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: [Anny Ondra, givenName, Anna]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07 
Target entity: Anna
Context triple: [Anny Ondra, 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 an actress known for portraying the ambitious and manipulative Lady Macbeth in a production of Shakespeare’s tragedy "Macbeth."
  • C. Anna
    Anna is a biblical figure in the Book of Tobit, known as Tobit's wife and the mother of Tobias.
  • D. Anna
    Anna is a woman whose full name is Mrs. Anna Smith.
  • E. Anna
    Anna of Moscow was a medieval Russian noblewoman and princess associated with the ruling dynasties of Muscovy.
  • 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: [Anny Ondra, givenName, Anna]
Generated description
Anna is the given first name of Anny Ondra, the Czech-Austrian film actress best known for her work in early European cinema and Alfred Hitchcock’s films.
NED2 Entity disambiguation (via description) gpt-5-mini-2025-08-07 
Target entity: Anna
Target entity description: Anna is the given first name of Anny Ondra, the Czech-Austrian film actress best known for her work in early European cinema and Alfred Hitchcock’s films.
  • A. Anna
    Anna is the given first name of the German Dada artist Hannah Höch, a pioneering figure in photomontage and avant-garde art.
  • 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 Anne Bancroft, the acclaimed American actress best known for her role as Mrs. Robinson in "The Graduate."
  • D. Anna
    Anna is the given first name of the American actress, comedian, and director Nancy Walker.
  • E. Anna
    Anna is the given first name of Eleanor Roosevelt, the influential former First Lady of the United States and human rights advocate.
  • 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_69d87f2171208190951025e526947816 completed April 10, 2026, 4:40 a.m.
NER Named-entity recognition batch_69e24594f23c8190bd59fcb2585cb5e3 completed April 17, 2026, 2:37 p.m.
NED1 Entity disambiguation (via context triple) batch_6a000ed338f48190a8a7280f7d2b112c completed May 10, 2026, 4:51 a.m.
NEDg Description generation batch_6a0010df563c8190be89a66f23a6d8c6 completed May 10, 2026, 5 a.m.
NED2 Entity disambiguation (via description) batch_6a0011559b748190ad406263889514a4 completed May 10, 2026, 5:02 a.m.
Created at: April 10, 2026, 5:04 a.m.