Triple

T1422985
Position Surface form Disambiguated ID Type / Status
Subject Mary (Polly) Prince E30265 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 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 (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
    Mary is the birth name of American actress, singer, and dancer Debbie Reynolds, a major Hollywood star of the mid-20th century.
  • B. Mary
    Mary is the given first name of the acclaimed American actress Meryl Streep.
  • C. 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.
  • D. 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.
  • E. 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.
  • 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_69a498fb823c8190a67ce4c4837e641a completed March 1, 2026, 7:52 p.m.
NER Named-entity recognition batch_69a4c4ba798881909c2259987248b030 completed March 1, 2026, 10:59 p.m.
NED1 Entity disambiguation (via context triple) batch_69add1a428b88190a79a669ca6b73671 completed March 8, 2026, 7:44 p.m.
NEDg Description generation batch_69add21921e0819090a7f39d17d86b23 completed March 8, 2026, 7:46 p.m.
NED2 Entity disambiguation (via description) batch_69add28d2ca881908ada32b73fdb3c6f completed March 8, 2026, 7:48 p.m.
Created at: March 1, 2026, 8 p.m.