Triple

T14378942
Position Surface form Disambiguated ID Type / Status
Subject Alice Englert E356548 entity
Predicate hasRole P161 FINISHED
Object Mary
Mary is a character portrayed by actress and filmmaker Alice Englert.
E1094681 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: [Alice Englert, hasRole, Mary]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Mary
Context triple: [Alice Englert, hasRole, 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: [Alice Englert, hasRole, Mary]
Generated description
Mary is a character portrayed by actress and filmmaker Alice Englert.
NED2 Entity disambiguation (via description) gpt-5-mini-2025-08-07
Target entity: Mary
Target entity description: Mary is a character portrayed by actress and filmmaker Alice Englert.
  • A. Mary
    Mary is a fictional character portrayed by British actress Gemma Jones, known for her nuanced performances in film and television.
  • B. Mary
    Mary is the birth name of Australian actress Rose Byrne, known for her roles in films like "Bridesmaids" and the "X-Men" series.
  • C. Mary
    Mary is the given name of American actress and singer-songwriter Mare Winningham, known for her work in film, television, and music.
  • D. Mary
    Mary is the given first name of American actress Elle Fanning, known for her roles in films like "Super 8" and the series "The Great."
  • E. Mary
    Mary is the given name of American character actress Marjorie Main, known for her roles in classic Hollywood films.
  • 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_69d8279163a081908aec45c0e3f1e02f completed April 9, 2026, 10:26 p.m.
NER Named-entity recognition batch_69de900a67e08190ab1dcf36e6bb3405 completed April 14, 2026, 7:05 p.m.
NED1 Entity disambiguation (via context triple) batch_69fd4c4145c081909832e2334a064fb0 completed May 8, 2026, 2:36 a.m.
NEDg Description generation batch_69fd4d1415908190a04713f504491387 completed May 8, 2026, 2:40 a.m.
NED2 Entity disambiguation (via description) batch_69fd4da8af2c8190ad3e78bbe1c9cd7a completed May 8, 2026, 2:42 a.m.
Created at: April 10, 2026, 1:16 a.m.