Triple

T838631
Position Surface form Disambiguated ID Type / Status
Subject Michael Gough E18125 entity
Predicate spouse P13 FINISHED
Object Henrietta Gough
Henrietta Gough was the wife of English actor Michael Gough, known for his prolific work in film, television, and theatre.
 E188898 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: Henrietta Gough | Statement: [Michael Gough, spouse, Henrietta Gough]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07 
Target entity: Henrietta Gough
Context triple: [Michael Gough, spouse, Henrietta Gough]
  • A. Harriet Burrow
    Harriet Burrow was the mother of the influential British philosopher and political economist John Stuart Mill.
  • B. Henrietta Edwards
    Henrietta Edwards was the wife of American inventor Eli Whitney, known for his creation of the cotton gin.
  • C. Harriet Pitt
    Harriet Pitt was an 18th-century British actress known for her work on the London stage and as the mother of actor and playwright Charles Dibdin the younger.
  • D. Harriet Pitt
    Harriet Pitt was an 18th-century British actress and the daughter of statesman William Pitt the Elder.
  • E. Harriet Eckersall
    Harriet Eckersall was the wife of the influential British economist and demographer Thomas Robert Malthus.
  • 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: Henrietta Gough
Triple: [Michael Gough, spouse, Henrietta Gough]
Generated description
Henrietta Gough was the wife of English actor Michael Gough, known for his prolific work in film, television, and theatre.
NED2 Entity disambiguation (via description) gpt-5-mini-2025-08-07 
Target entity: Henrietta Gough
Target entity description: Henrietta Gough was the wife of English actor Michael Gough, known for his prolific work in film, television, and theatre.
  • A. Harriet Burrow
    Harriet Burrow was the mother of the influential British philosopher and political economist John Stuart Mill.
  • B. Henrietta Edwards
    Henrietta Edwards was the wife of American inventor Eli Whitney, known for his creation of the cotton gin.
  • C. Harriet Pitt
    Harriet Pitt was an 18th-century British actress known for her work on the London stage and as the mother of actor and playwright Charles Dibdin the younger.
  • D. Harriet Pitt
    Harriet Pitt was an 18th-century British actress and the daughter of statesman William Pitt the Elder.
  • E. Harriet Eckersall
    Harriet Eckersall was the wife of the influential British economist and demographer Thomas Robert Malthus.
  • 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_69a49389f44881909a608fb27d89f247 completed March 1, 2026, 7:29 p.m.
NER Named-entity recognition batch_69a4abd0e8bc8190afe29cd4745c2f86 completed March 1, 2026, 9:12 p.m.
NED1 Entity disambiguation (via context triple) batch_69ad717a95848190964e7cf1be92ad67 completed March 8, 2026, 12:54 p.m.
NEDg Description generation batch_69ad72016c3c8190ac3bd11bab59fdf0 completed March 8, 2026, 12:56 p.m.
NED2 Entity disambiguation (via description) batch_69ad7277b5f081908a8af047032aa15a completed March 8, 2026, 12:58 p.m.
Created at: March 1, 2026, 7:38 p.m.