Triple

T13000509
Position Surface form Disambiguated ID Type / Status
Subject Mary (novel) E322156 entity
Predicate hasTitle P38 FINISHED
Object Mary
Mary is a 1927 psychological novel by Vladimir Nabokov that explores memory, exile, and lost love through the reflections of a Russian émigré in Berlin.
E1015590 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: Mary | Statement: [Mary (novel), hasTitle, Mary]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Mary
Context triple: [Mary (novel), hasTitle, Mary]
  • A. Mary
    Mary is the given name of the American suspense novelist Mary Higgins Clark, known for her bestselling mystery and thriller books.
  • B. Mary
    Mary is the given name of Mary Catherine Bateson, an American cultural anthropologist and writer known for her work on learning and the human life cycle.
  • C. Mary
    Mary of Lancaster was a 14th-century English noblewoman, daughter of Henry, 3rd Earl of Lancaster, and a member of the influential House of Lancaster.
  • D. Mary
    Mary is the middle name of Joseph Plunkett, the Irish nationalist, poet, and 1916 Easter Rising leader.
  • E. Mary
    Mary is the birth name of American actress, comedian, and writer Lily Tomlin, known for her groundbreaking work in television, film, and theater.
  • 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: Mary
Triple: [Mary (novel), hasTitle, Mary]
Generated description
Mary is a 1927 psychological novel by Vladimir Nabokov that explores memory, exile, and lost love through the reflections of a Russian émigré in Berlin.
NED2 Entity disambiguation (via description) gpt-5-mini-2025-08-07
Target entity: Mary
Target entity description: Mary is a 1927 psychological novel by Vladimir Nabokov that explores memory, exile, and lost love through the reflections of a Russian émigré in Berlin.
  • A. Mary
    "Mary" is a 1949 novel by Polish-Jewish writer Sholem Asch that reimagines the life of Jesus through the perspective of his mother.
  • B. Mary
    Mary is a fictional character in B.F. Skinner’s utopian novel "Walden Two," representing one of the community’s young members shaped by its behaviorist social principles.
  • C. Mary
    Mary is the given name of the American suspense novelist Mary Higgins Clark, known for her bestselling mystery and thriller books.
  • D. Mary
    Mary is a central character in W. H. Auden’s long poem "For the Time Being," which reimagines the Nativity story in a modern, philosophical context.
  • E. Mary
    Mary is the central protagonist of the play "The Memory of Water," around whom the story’s emotional and familial conflicts revolve.
  • 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_69d807657e8c8190bd9435ee2f823845 completed April 9, 2026, 8:09 p.m.
NER Named-entity recognition batch_69d97e9828748190b2ad9ea29180b7d3 completed April 10, 2026, 10:50 p.m.
NED1 Entity disambiguation (via context triple) batch_69f6c0f95c548190a6fc2c1ea98246c3 completed May 3, 2026, 3:28 a.m.
NEDg Description generation batch_69f6c34532148190a0c609ff085e359c completed May 3, 2026, 3:38 a.m.
NED2 Entity disambiguation (via description) batch_69f6c3c6b240819099310f50cc7eabca completed May 3, 2026, 3:40 a.m.
Created at: April 9, 2026, 8:46 p.m.