Triple

T15496701
Position Surface form Disambiguated ID Type / Status
Subject Sarah Sutherland E378835 entity
Predicate givenName P17 FINISHED
Object Sarah
Sarah is a feminine given name of Hebrew origin, commonly interpreted to mean "princess" and widely used in many cultures and languages.
 E954385 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: [Sarah Sutherland, givenName, Sarah]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07 
Target entity: Sarah
Context triple: [Sarah Sutherland, givenName, Sarah]
  • A. Sarah
    Sarah is the central protagonist of the story "Horse Girl," around whom the main narrative and character development revolve.
  • B. Sarah
    Sarah is a person whose full name is Sarah Catherine McPherson Risher Getty.
  • 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: [Sarah Sutherland, givenName, Sarah]
Generated description
Sarah is a feminine given name of Hebrew origin, commonly interpreted to mean "princess" and widely used in many cultures and languages.
NED2 Entity disambiguation (via description) gpt-5-mini-2025-08-07 
Target entity: Sarah
Target entity description: Sarah is a feminine given name of Hebrew origin, commonly interpreted to mean "princess" and widely used in many cultures and languages.
  • A. Sarah chosen
    Sarah is a female given name of Hebrew origin, commonly used in English-speaking countries and traditionally meaning "princess."
  • B. Sarah
    Sarah is a key matriarch in the Hebrew Bible, revered as the wife of Abraham and mother of Isaac in the Jewish, Christian, and Islamic traditions.
  • C. 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."
  • D. Sarah
    Sarah is the given name of Sarah Moore Grimké, a prominent 19th-century American abolitionist, women's rights advocate, and writer.
  • E. Sarah
    Sarah is the given name of Sarah Jane Negley Mellon, a prominent American socialite and philanthropist from the influential Mellon family.
  • 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_69d85cd53a7c819080f5b9042c4c199e completed April 10, 2026, 2:13 a.m.
NER Named-entity recognition batch_69e03faecd60819091eeaa56c9c8f67d completed April 16, 2026, 1:47 a.m.
NED1 Entity disambiguation (via context triple) batch_69ff3d48f17c819088c4d8c2d2b368c8 completed May 9, 2026, 1:57 p.m.
NEDg Description generation batch_69ff3f59213c8190a9c98350225b5151 completed May 9, 2026, 2:06 p.m.
NED2 Entity disambiguation (via description) batch_69ff3ff96a6c8190a4c9f20dabc86cef completed May 9, 2026, 2:08 p.m.
Created at: April 10, 2026, 3:52 a.m.