Triple

T20157158
Position Surface form Disambiguated ID Type / Status
Subject PEN/Jean Stein Book Award E491601 entity
Predicate namedAfter P63 FINISHED
Object Jean Stein
Jean Stein was an American author and oral historian known for her innovative interview-based books and influential role in New York’s literary and cultural circles.
E1414866 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: Jean Stein | Statement: [PEN/Jean Stein Book Award, namedAfter, Jean Stein]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Jean Stein
Context triple: [PEN/Jean Stein Book Award, namedAfter, Jean Stein]
  • A. Ruth Franklin
    Ruth Franklin is an American literary critic and biographer best known for her acclaimed biography of novelist Shirley Jackson.
  • B. Jane Pollack
    Jane Pollack is known as the former wife of American character actor Lance Henriksen.
  • C. Vivian Janis
    Vivian Janis was an American actress best known for her work in mid-20th-century film and television and for her marriage to actor Robert Cummings.
  • D. Jane Elaine Schook
    Jane Elaine Schook was the mother of American playwright and actor Sam Shepard.
  • E. Beverly Gage
    Beverly Gage is an American historian and Yale professor known for her scholarship on 20th-century U.S. political history and her acclaimed biography of FBI director J. Edgar Hoover.
  • 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: Jean Stein
Triple: [PEN/Jean Stein Book Award, namedAfter, Jean Stein]
Generated description
Jean Stein was an American author and oral historian known for her innovative interview-based books and influential role in New York’s literary and cultural circles.
NED2 Entity disambiguation (via description) gpt-5-mini-2025-08-07
Target entity: Jean Stein
Target entity description: Jean Stein was an American author and oral historian known for her innovative interview-based books and influential role in New York’s literary and cultural circles.
  • A. Ruth Franklin
    Ruth Franklin is an American literary critic and biographer best known for her acclaimed biography of novelist Shirley Jackson.
  • B. Jane Pollack
    Jane Pollack is known as the former wife of American character actor Lance Henriksen.
  • C. Vivian Janis
    Vivian Janis was an American actress best known for her work in mid-20th-century film and television and for her marriage to actor Robert Cummings.
  • D. Jane Elaine Schook
    Jane Elaine Schook was the mother of American playwright and actor Sam Shepard.
  • E. Beverly Gage
    Beverly Gage is an American historian and Yale professor known for her scholarship on 20th-century U.S. political history and her acclaimed biography of FBI director J. Edgar Hoover.
  • 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_69da6265f8f0819080b29c752a574088 completed April 11, 2026, 3:01 p.m.
NER Named-entity recognition batch_69e667e18a0c8190a2cc2b305da28047 completed April 20, 2026, 5:52 p.m.
NED1 Entity disambiguation (via context triple) batch_6a083476e2d08190807674e3f61382bc completed May 16, 2026, 9:10 a.m.
NEDg Description generation batch_6a08351511888190a144ff037abdddfb completed May 16, 2026, 9:12 a.m.
NED2 Entity disambiguation (via description) batch_6a0835e4248c8190817907ca46cd5cff completed May 16, 2026, 9:16 a.m.
Created at: April 11, 2026, 11:34 p.m.