Triple

T9720930
Position Surface form Disambiguated ID Type / Status
Subject Saeed Jaffrey E235467 entity
Predicate spouse P13 FINISHED
Object Jennifer Sorrell
Jennifer Sorrell is best known as the wife of acclaimed Indian-British actor Saeed Jaffrey.
E856872 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: Jennifer Sorrell | Statement: [Saeed Jaffrey, spouse, Jennifer Sorrell]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Jennifer Sorrell
Context triple: [Saeed Jaffrey, spouse, Jennifer Sorrell]
  • A. Angela Quarles
    Angela Quarles is a contemporary American author best known for her time-travel and paranormal romance novels.
  • B. Larissa Weems
    Larissa Weems is a character from the Netflix series "Wednesday," serving as the poised and enigmatic principal of Nevermore Academy.
  • C. Cynthia Solomon
    Cynthia Solomon is a pioneering computer scientist and educator best known for her foundational work in the development of educational programming languages for children, including co-creating Logo.
  • D. Tracey Davis
    Tracey Davis was an American author and the daughter of legendary entertainer Sammy Davis Jr., known for writing about her father's life and their complex family relationship.
  • E. Laura Harris
    Laura Harris is a Canadian actress known for her roles in films like "The Faculty" and TV series such as "24" and "Dead Like Me."
  • 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: Jennifer Sorrell
Triple: [Saeed Jaffrey, spouse, Jennifer Sorrell]
Generated description
Jennifer Sorrell is best known as the wife of acclaimed Indian-British actor Saeed Jaffrey.
NED2 Entity disambiguation (via description) gpt-5-mini-2025-08-07
Target entity: Jennifer Sorrell
Target entity description: Jennifer Sorrell is best known as the wife of acclaimed Indian-British actor Saeed Jaffrey.
  • A. Angela Quarles
    Angela Quarles is a contemporary American author best known for her time-travel and paranormal romance novels.
  • B. Larissa Weems
    Larissa Weems is a character from the Netflix series "Wednesday," serving as the poised and enigmatic principal of Nevermore Academy.
  • C. Cynthia Solomon
    Cynthia Solomon is a pioneering computer scientist and educator best known for her foundational work in the development of educational programming languages for children, including co-creating Logo.
  • D. Tracey Davis
    Tracey Davis was an American author and the daughter of legendary entertainer Sammy Davis Jr., known for writing about her father's life and their complex family relationship.
  • E. Laura Harris
    Laura Harris is a Canadian actress known for her roles in films like "The Faculty" and TV series such as "24" and "Dead Like Me."
  • 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_69ca84d0123c819096f9dc3b6abb0881 completed March 30, 2026, 2:12 p.m.
NER Named-entity recognition batch_69cd9e419c2c8190b325d5fd692c6000 completed April 1, 2026, 10:37 p.m.
NED1 Entity disambiguation (via context triple) batch_69d74fb63b7081909cb6faddd795ced6 completed April 9, 2026, 7:05 a.m.
NEDg Description generation batch_69d751122d208190abaa4fd72a07643b completed April 9, 2026, 7:11 a.m.
NED2 Entity disambiguation (via description) batch_69d751d4aa908190a825322ebf0066af completed April 9, 2026, 7:14 a.m.
Created at: March 30, 2026, 8:20 p.m.