Triple

T3907440
Position Surface form Disambiguated ID Type / Status
Subject Mary Allerton E87235 entity
Predicate givenName P17 FINISHED
Object Mary
Mary Allerton was a Mayflower passenger and one of the early settlers of Plymouth Colony in 17th-century New England.
E398976 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 Allerton, givenName, Mary]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Mary
Context triple: [Mary Allerton, givenName, Mary]
  • A. Mary
    Mary is a central figure in Christianity, venerated as the mother of Jesus and often honored as the Virgin Mary.
  • B. Mary
    Mary is the given first name of Margaret Truman, the daughter of U.S. President Harry S. Truman and a noted author and singer.
  • C. Mary
    Mary is the given first name of the acclaimed American actress Meryl Streep.
  • D. Mary
    Mary is a minor character in Mark Twain's novel "The Adventures of Tom Sawyer," known as Tom's kind and well-behaved cousin.
  • E. Mary
    Mary Eleanor Darwin was a member of the Darwin family, known primarily as a descendant of the naturalist Charles Darwin.
  • 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 Allerton, givenName, Mary]
Generated description
Mary Allerton was a Mayflower passenger and one of the early settlers of Plymouth Colony in 17th-century New England.
NED2 Entity disambiguation (via description) gpt-5-mini-2025-08-07
Target entity: Mary
Target entity description: Mary Allerton was a Mayflower passenger and one of the early settlers of Plymouth Colony in 17th-century New England.
  • A. Mary
    Mary II of England was a late 17th-century Queen of England, Scotland, and Ireland who ruled jointly with her husband William III after the Glorious Revolution.
  • B. Mary
    Mary is the birth name of May Morris, the English artisan, designer, and key figure in the Arts and Crafts movement.
  • 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, Princess Royal and Princess of Orange, was the eldest daughter of King Charles I of England and the wife of William II of Orange, making her a key figure in 17th-century Anglo-Dutch royal relations.
  • E. Mary
    Mary is the given name of Mary Church Terrell, a prominent African American civil rights activist, educator, and suffragist in the late 19th and early 20th centuries.
  • 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_69aed9424514819086e9c58adde6652d completed March 9, 2026, 2:29 p.m.
NER Named-entity recognition batch_69aeed1290e48190aaf2d8b2a7be707a completed March 9, 2026, 3:53 p.m.
NED1 Entity disambiguation (via context triple) batch_69b52845684c8190b6f0676319a6fc3c completed March 14, 2026, 9:20 a.m.
NEDg Description generation batch_69b5290462a88190892c0bcc3a74f2fa completed March 14, 2026, 9:23 a.m.
NED2 Entity disambiguation (via description) batch_69b529600884819098cb208e38e6281a completed March 14, 2026, 9:24 a.m.
Created at: March 9, 2026, 3:22 p.m.