Triple

T14011775
Position Surface form Disambiguated ID Type / Status
Subject Ellen Mary Marcy E337096 entity
Predicate middleName P143 FINISHED
Object Mary
Mary is a feminine given name of Hebrew origin, widely used in English-speaking countries and historically associated with numerous religious and cultural 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: [Ellen Mary Marcy, middleName, Mary]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Mary
Context triple: [Ellen Mary Marcy, middleName, 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: [Ellen Mary Marcy, middleName, Mary]
Generated description
Mary is a feminine given name of Hebrew origin, widely used in English-speaking countries and historically associated with numerous religious and cultural 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, widely used in English-speaking countries and historically associated with numerous religious and cultural 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 Wollstonecraft, the pioneering 18th-century English writer and advocate of women's rights.
  • C. Mary
    Mary is a central figure in Christianity, venerated as the mother of Jesus and often honored as the Virgin Mary.
  • D. Mary
    Mary is the given name of Mary Sidney, an English Renaissance noblewoman, writer, and literary patron.
  • E. Mary
    Mary is the given name of Mary Tyler Peabody, an American educator and reformer known for her work in the 19th century.
  • 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_69d81c645c5c8190b1fd16a285a1b78a completed April 9, 2026, 9:38 p.m.
NER Named-entity recognition batch_69de2ed5cfd0819085b9c860b119a9de completed April 14, 2026, 12:11 p.m.
NED1 Entity disambiguation (via context triple) batch_69fbac9604cc819088cde0ad8271ad48 completed May 6, 2026, 9:03 p.m.
NEDg Description generation batch_69fbad35be6c8190aa329fa947cbdcd9 completed May 6, 2026, 9:05 p.m.
NED2 Entity disambiguation (via description) batch_69fbae42ef2c8190b653d95de94042bc completed May 6, 2026, 9:10 p.m.
Created at: April 9, 2026, 10:19 p.m.