Triple

T17321967
Position Surface form Disambiguated ID Type / Status
Subject Mary Brown Austin E420582 entity
Predicate givenName P17 FINISHED
Object Mary
Mary is a feminine given name of Hebrew origin that has been widely used across cultures and history, often associated with religious and literary figures.
E75782 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 Brown Austin, givenName, Mary]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Mary
Context triple: [Mary Brown Austin, givenName, Mary]
  • A. Mary
    Mary is the given name of Mary Jo Kopechne, the American political campaign specialist who died in the 1969 Chappaquiddick incident involving Senator Ted Kennedy.
  • B. Mary
    Mary is the middle name of Edith Tolkien, the wife of author J.R.R. Tolkien.
  • C. Mary
    Mary is the central protagonist of the play "The Memory of Water," around whom the story’s emotional and familial conflicts revolve.
  • D. Mary
    Mary is the birth name of American actress, comedian, and writer Lily Tomlin, known for her groundbreaking work in television, film, and theater.
  • E. Mary
    Mary is the given name of the American stage and film actress Josephine Hull, known for her roles in classic mid-20th-century theater and cinema.
  • 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 Brown Austin, givenName, Mary]
Generated description
Mary is a feminine given name of Hebrew origin that has been widely used across cultures and history, often associated with religious and literary figures.
NED2 Entity disambiguation (via description) gpt-5-mini-2025-08-07
Target entity: Mary
Target entity description: Mary is a feminine given name of Hebrew origin that has been widely used across cultures and history, often associated with religious and literary figures.
  • A. Mary chosen
    Mary is a feminine given name of Hebrew origin, widely used in English-speaking and many other cultures and historically associated with numerous religious and historical figures.
  • B. Mary
    Mary is the given name of Mary Sidney, an English Renaissance noblewoman, writer, and literary patron.
  • C. Mary
    Mary is the given name of Mary Wollstonecraft, the pioneering 18th-century English writer and advocate of women's rights.
  • D. Mary
    Mary is a central figure in Christianity, venerated as the mother of Jesus and often honored as the Virgin Mary.
  • E. Mary
    Mary is the given name of Mary Anne Galton, a historical figure known primarily through her familial and biographical associations.
  • 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_69d889d22b848190a4663d0b8f8f76e7 completed April 10, 2026, 5:25 a.m.
NER Named-entity recognition batch_69e439d01e2c8190a358dace420d4575 completed April 19, 2026, 2:11 a.m.
NED1 Entity disambiguation (via context triple) batch_6a01954cfd048190b201c5e457c2a4a2 completed May 11, 2026, 8:37 a.m.
NEDg Description generation batch_6a019b79d7148190abf4b41f0c84c62e completed May 11, 2026, 9:03 a.m.
NED2 Entity disambiguation (via description) batch_6a019c1b60f08190a6469602751e3471 completed May 11, 2026, 9:06 a.m.
Created at: April 10, 2026, 5:43 a.m.