Triple

T8760140
Position Surface form Disambiguated ID Type / Status
Subject Mary (Polly) Prince E208175 entity
Predicate givenName P17 FINISHED
Object Mary
Mary (Polly) Prince is a fictional character best known as the free-spirited, adventurous love interest played by Jennifer Aniston in the romantic comedy film "Along Came Polly."
E208175 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 (Polly) Prince, givenName, Mary]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Mary
Context triple: [Mary (Polly) Prince, givenName, Mary]
  • A. 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.
  • B. Mary
    Mary is the birth name of American actress, singer, and dancer Debbie Reynolds, a major Hollywood star of the mid-20th century.
  • C. Mary
    Mary is the middle name of Katherine Mary Dewar, a component of her full personal name.
  • D. Mary
    Mary is the given name of Mary J. Blige, the acclaimed American singer, songwriter, and actress often called the "Queen of Hip-Hop Soul."
  • E. 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.
  • 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 (Polly) Prince, givenName, Mary]
Generated description
Mary (Polly) Prince is a fictional character best known as the free-spirited, adventurous love interest played by Jennifer Aniston in the romantic comedy film "Along Came Polly."
NED2 Entity disambiguation (via description) gpt-5-mini-2025-08-07
Target entity: Mary
Target entity description: Mary (Polly) Prince is a fictional character best known as the free-spirited, adventurous love interest played by Jennifer Aniston in the romantic comedy film "Along Came Polly."
  • A. Mary chosen
    Mary (Polly) Prince is a fictional character best known as the free-spirited, adventurous love interest played by Jennifer Aniston in the romantic comedy film "Along Came Polly."
  • B. Mary
    Mary is a central character in the romantic comedy film "About Time," known for her warm, quirky personality and her relationship with the time-traveling protagonist.
  • C. Mary
    Mary is a fictional character portrayed by British actress Gemma Jones, known for her nuanced performances in film and television.
  • D. Mary
    Mary is the given name of Lady Mary Palliser, a fictional aristocratic character from Anthony Trollope’s Palliser novels.
  • 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.

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_69ca835df7e08190ac875664cca8f9ca completed March 30, 2026, 2:06 p.m.
NER Named-entity recognition batch_69cc5df9729481908679151988b76d2f completed March 31, 2026, 11:51 p.m.
NED1 Entity disambiguation (via context triple) batch_69cf6f10aea48190bb63a4b2fdd72338 completed April 3, 2026, 7:41 a.m.
NEDg Description generation batch_69cf7041b6bc81909924d1382b756746 completed April 3, 2026, 7:46 a.m.
NED2 Entity disambiguation (via description) batch_69cf714f22c48190a192c6fc32debfd6 completed April 3, 2026, 7:50 a.m.
Created at: March 30, 2026, 6:40 p.m.