Triple

T11898646
Position Surface form Disambiguated ID Type / Status
Subject Bastard E283095 entity
Predicate hasPart P35 FINISHED
Object Sarah
Sarah is a character associated with the work "Bastard," likely serving as a notable figure within its story.
E954292 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: Sarah | Statement: [Bastard, hasPart, Sarah]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Sarah
Context triple: [Bastard, hasPart, Sarah]
  • A. Sarah
    Sarah is the given first name of the actress and comedian Patsy Kelly.
  • B. Sarah
    Sarah is the given name of American actress Sarah Paulson, known for her versatile roles in film and television, particularly in "American Horror Story" and "The People v. O. J. Simpson."
  • C. Sarah
    Sarah is the given name of Sarah P. Duke, the philanthropist and namesake of Duke University's Sarah P. Duke Gardens.
  • D. Sarah
    Sarah is the given name of the renowned 19th- and early 20th-century French stage actress Sarah Bernhardt, often called "the Divine Sarah."
  • E. Sarah
    Sarah Onyango Obama was the Kenyan educator and philanthropist best known as the step-grandmother of former U.S. President Barack Obama.
  • 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: Sarah
Triple: [Bastard, hasPart, Sarah]
Generated description
Sarah is a character associated with the work "Bastard," likely serving as a notable figure within its story.
NED2 Entity disambiguation (via description) gpt-5-mini-2025-08-07
Target entity: Sarah
Target entity description: Sarah is a character associated with the work "Bastard," likely serving as a notable figure within its story.
  • A. Sarah
    Sarah is a fictional character from the musical "Ragtime," representing the struggles and resilience of African Americans in early 20th-century America.
  • B. Sarah
    Sarah is a fictional character from the 1992 British comedy-drama film "Peter’s Friends," which follows a group of Cambridge university friends reuniting after a decade.
  • C. Sarah
    Sarah is the given name of Australian actress Sarah Snook, known for her acclaimed role in the television series "Succession."
  • D. Sarah
    Sarah is the given first name of American actress and model Margaret Qualley, known for roles in projects like "Maid" and "Once Upon a Time in Hollywood."
  • E. Sarah
    Sarah is an alternate given name associated with Sally Hemings, the enslaved woman of mixed race owned by Thomas Jefferson and central to historical discussions of slavery and Jefferson’s legacy.
  • 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_69d6ab2a90b08190a4e818821cc93e6d completed April 8, 2026, 7:23 p.m.
NER Named-entity recognition batch_69d8dd13cc10819089d8d5103e562924 completed April 10, 2026, 11:20 a.m.
NED1 Entity disambiguation (via context triple) batch_69f43ff588f08190affc45b44b9e85e3 completed May 1, 2026, 5:53 a.m.
NEDg Description generation batch_69f448f506a48190a0f1b89ad570fad5 completed May 1, 2026, 6:32 a.m.
NED2 Entity disambiguation (via description) batch_69f44ad185cc8190893cf663cfed6980 completed May 1, 2026, 6:40 a.m.
Created at: April 8, 2026, 9:44 p.m.