Triple

T2128791
Position Surface form Disambiguated ID Type / Status
Subject Chambers E46486 entity
Predicate hasNotableBearer P458 FINISHED
Object Ethel Chambers
Ethel Chambers is a notable individual who shares the Chambers surname and is recognized as a distinguished bearer of that family name.
 E308836 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: Ethel Chambers | Statement: [Chambers, hasNotableBearer, Ethel Chambers]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07 
Target entity: Ethel Chambers
Context triple: [Chambers, hasNotableBearer, Ethel Chambers]
  • A. Henrietta Gough
    Henrietta Gough was the wife of English actor Michael Gough, known for his prolific work in film, television, and theatre.
  • B. Harriet Burrow
    Harriet Burrow was the mother of the influential British philosopher and political economist John Stuart Mill.
  • C. Margaret Gamage
    Margaret Gamage was a 16th-century Welsh noblewoman of the Gamage family who became Countess of Nottingham through her marriage into the English Howard dynasty.
  • D. Edith Luckett
    Edith Luckett was an American stage actress best known as the mother of Nancy Reagan, the future First Lady of the United States.
  • E. Betty Furness
    Betty Furness was an American actress and television personality best known for her film roles in the 1930s and later as a pioneering consumer affairs advocate on TV.
  • 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: Ethel Chambers
Triple: [Chambers, hasNotableBearer, Ethel Chambers]
Generated description
Ethel Chambers is a notable individual who shares the Chambers surname and is recognized as a distinguished bearer of that family name.
NED2 Entity disambiguation (via description) gpt-5-mini-2025-08-07 
Target entity: Ethel Chambers
Target entity description: Ethel Chambers is a notable individual who shares the Chambers surname and is recognized as a distinguished bearer of that family name.
  • A. Henrietta Gough
    Henrietta Gough was the wife of English actor Michael Gough, known for his prolific work in film, television, and theatre.
  • B. Harriet Burrow
    Harriet Burrow was the mother of the influential British philosopher and political economist John Stuart Mill.
  • C. Margaret Gamage
    Margaret Gamage was a 16th-century Welsh noblewoman of the Gamage family who became Countess of Nottingham through her marriage into the English Howard dynasty.
  • D. Edith Luckett
    Edith Luckett was an American stage actress best known as the mother of Nancy Reagan, the future First Lady of the United States.
  • E. Betty Furness
    Betty Furness was an American actress and television personality best known for her film roles in the 1930s and later as a pioneering consumer affairs advocate on TV.
  • 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_69a88a1626548190ae59a5028c3baa8e completed March 4, 2026, 7:37 p.m.
NER Named-entity recognition batch_69abbb7659f48190871cb27faf47e18a completed March 7, 2026, 5:45 a.m.
NED1 Entity disambiguation (via context triple) batch_69b0559265388190b070de8b92c6e95b completed March 10, 2026, 5:32 p.m.
NEDg Description generation batch_69b05f7e78e8819095185f170ca26bda completed March 10, 2026, 6:14 p.m.
NED2 Entity disambiguation (via description) batch_69b0617a21a881909a0f52268a2494a6 completed March 10, 2026, 6:22 p.m.
Created at: March 4, 2026, 7:44 p.m.