Triple

T10782855
Position Surface form Disambiguated ID Type / Status
Subject Norma Besant E254371 entity
Predicate hasLoveInterest P7325 FINISHED
Object Michael Jeffrey
Michael Jeffrey is a fictional character known primarily as the love interest of Norma Besant.
 E885750 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: Michael Jeffrey | Statement: [Norma Besant, hasLoveInterest, Michael Jeffrey]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07 
Target entity: Michael Jeffrey
Context triple: [Norma Besant, hasLoveInterest, Michael Jeffrey]
  • A. John Whitesell
    John Whitesell is an American television and film director and producer known for his work on various TV series and feature comedies.
  • B. Michael James
    Michael James is the womanizing psychiatrist protagonist of the 1965 romantic comedy film "What’s New Pussycat?".
  • C. Michael Spencer Jones
    Michael Spencer Jones is a British rock photographer best known for creating many of Oasis’s iconic album covers and promotional images during the 1990s.
  • D. John Curtis Estes
    John Curtis Estes is the birth name of John Holmes, a notorious American adult film actor who became one of the most famous pornographic performers of the 1970s and 1980s.
  • E. James Seymour
    James Seymour was an American screenwriter active during Hollywood's early sound era, contributing to several notable studio films in the 1930s.
  • 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: Michael Jeffrey
Triple: [Norma Besant, hasLoveInterest, Michael Jeffrey]
Generated description
Michael Jeffrey is a fictional character known primarily as the love interest of Norma Besant.
NED2 Entity disambiguation (via description) gpt-5-mini-2025-08-07 
Target entity: Michael Jeffrey
Target entity description: Michael Jeffrey is a fictional character known primarily as the love interest of Norma Besant.
  • A. John Whitesell
    John Whitesell is an American television and film director and producer known for his work on various TV series and feature comedies.
  • B. Michael James
    Michael James is the womanizing psychiatrist protagonist of the 1965 romantic comedy film "What’s New Pussycat?".
  • C. Michael Spencer Jones
    Michael Spencer Jones is a British rock photographer best known for creating many of Oasis’s iconic album covers and promotional images during the 1990s.
  • D. John Curtis Estes
    John Curtis Estes is the birth name of John Holmes, a notorious American adult film actor who became one of the most famous pornographic performers of the 1970s and 1980s.
  • E. James Seymour
    James Seymour was an American screenwriter active during Hollywood's early sound era, contributing to several notable studio films in the 1930s.
  • 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_69d6aa609f008190a294200aefcb7bd5 completed April 8, 2026, 7:20 p.m.
NER Named-entity recognition batch_69d732c5618081908f72838ed42ed05c completed April 9, 2026, 5:01 a.m.
NED1 Entity disambiguation (via context triple) batch_69de55fbfc70819098eb40cf0d1b9e8c completed April 14, 2026, 2:58 p.m.
NEDg Description generation batch_69de5eadb9448190bdf69711394e2ab7 completed April 14, 2026, 3:35 p.m.
NED2 Entity disambiguation (via description) batch_69de607917808190922df6521d7bfb07 completed April 14, 2026, 3:42 p.m.
Created at: April 8, 2026, 9:17 p.m.