Triple

T12866940
Position Surface form Disambiguated ID Type / Status
Subject Anna of the Five Towns E307743 entity
Predicate hasTitleCharacter P5716 FINISHED
Object Anna
Anna is the central protagonist of Arnold Bennett’s novel "Anna of the Five Towns," a young woman navigating love, duty, and religious constraint in an industrial English setting.
 E1007342 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 of the Five Towns, hasTitleCharacter, Anna]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07 
Target entity: Anna
Context triple: [Anna of the Five Towns, hasTitleCharacter, 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 a key female resistance fighter in the World War II adventure film "The Guns of Navarone," whose complex loyalties and actions significantly impact the mission’s outcome.
  • C. Anna
    Anna is an actress known for portraying the ambitious and manipulative Lady Macbeth in a production of Shakespeare’s tragedy "Macbeth."
  • D. Anna
    Anna is a biblical figure in the Book of Tobit, known as Tobit's wife and the mother of Tobias.
  • 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: [Anna of the Five Towns, hasTitleCharacter, Anna]
Generated description
Anna is the central protagonist of Arnold Bennett’s novel "Anna of the Five Towns," a young woman navigating love, duty, and religious constraint in an industrial English setting.
NED2 Entity disambiguation (via description) gpt-5-mini-2025-08-07 
Target entity: Anna
Target entity description: Anna is the central protagonist of Arnold Bennett’s novel "Anna of the Five Towns," a young woman navigating love, duty, and religious constraint in an industrial English setting.
  • A. 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.
  • B. Anna
    Anna is a central fictional character in Michael Ondaatje's novel "Divisadero," around whom much of the story's emotional and narrative complexity revolves.
  • C. Anna
    Anna is a central character in Harold Pinter’s play "Old Times," embodying themes of memory, ambiguity, and the shifting nature of personal relationships.
  • D. Anna
    Anna is a biblical figure in the Book of Tobit, known as Tobit's wife and the mother of Tobias.
  • 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. 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_69d7bdf69bc48190af6c2621f28ca351 completed April 9, 2026, 2:55 p.m.
NER Named-entity recognition batch_69d9708e0b788190b72a3057e271c227 completed April 10, 2026, 9:50 p.m.
NED1 Entity disambiguation (via context triple) batch_69f69b88d7048190bb584aa48bba5288 completed May 3, 2026, 12:49 a.m.
NEDg Description generation batch_69f69c46a6208190a113aefbce1bbaac completed May 3, 2026, 12:52 a.m.
NED2 Entity disambiguation (via description) batch_69f69cead6d881909765424b5391a613 completed May 3, 2026, 12:55 a.m.
Created at: April 9, 2026, 5:38 p.m.