Triple

T787668
Position Surface form Disambiguated ID Type / Status
Subject Marilyn Monroe E16840 entity
Predicate spouse P13 FINISHED
Object James Dougherty
James Dougherty was an American police officer best known as the first husband of Marilyn Monroe before she became a famous actress.
E157862 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: James Dougherty | Statement: [Marilyn Monroe, spouse, James Dougherty]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: James Dougherty
Context triple: [Marilyn Monroe, spouse, James Dougherty]
  • A. Michael Callaghan
    Michael Callaghan is one of the children of former UK Prime Minister James Callaghan.
  • B. Kevin O'Connor
    Kevin O'Connor is an American entrepreneur best known as the co-founder and former CEO of the online advertising company DoubleClick.
  • C. Sean McDonough
    Sean McDonough is an American sportscaster best known for his long career calling Major League Baseball and college sports on national television.
  • D. John McGlynn
    John McGlynn is a Scottish football manager best known for his successful spells in charge of Raith Rovers.
  • E. Michael H. Moloney
    Michael H. Moloney is a physics-focused science policy and leadership professional who serves as the chief executive officer of the American Institute of Physics.
  • 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: James Dougherty
Triple: [Marilyn Monroe, spouse, James Dougherty]
Generated description
James Dougherty was an American police officer best known as the first husband of Marilyn Monroe before she became a famous actress.
NED2 Entity disambiguation (via description) gpt-5-mini-2025-08-07
Target entity: James Dougherty
Target entity description: James Dougherty was an American police officer best known as the first husband of Marilyn Monroe before she became a famous actress.
  • A. Michael Callaghan
    Michael Callaghan is one of the children of former UK Prime Minister James Callaghan.
  • B. Kevin O'Connor
    Kevin O'Connor is an American entrepreneur best known as the co-founder and former CEO of the online advertising company DoubleClick.
  • C. Sean McDonough
    Sean McDonough is an American sportscaster best known for his long career calling Major League Baseball and college sports on national television.
  • D. John McGlynn
    John McGlynn is a Scottish football manager best known for his successful spells in charge of Raith Rovers.
  • E. Michael H. Moloney
    Michael H. Moloney is a physics-focused science policy and leadership professional who serves as the chief executive officer of the American Institute of Physics.
  • 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_69a4936cb7448190914f5fe4b8d81607 completed March 1, 2026, 7:28 p.m.
NER Named-entity recognition batch_69a4a78171908190a38a70274bfbebf9 completed March 1, 2026, 8:54 p.m.
NED1 Entity disambiguation (via context triple) batch_69acd46422408190911e6eaec5866fe8 completed March 8, 2026, 1:44 a.m.
NEDg Description generation batch_69acd4fade9881908ed8e4598f4821f6 completed March 8, 2026, 1:46 a.m.
NED2 Entity disambiguation (via description) batch_69acd55b90608190a5ff734af6264ab5 completed March 8, 2026, 1:48 a.m.
Created at: March 1, 2026, 7:38 p.m.