Triple

T21319268
Position Surface form Disambiguated ID Type / Status
Subject Miriam Grant E525566 entity
Predicate familyName P18 FINISHED
Object Grant
Grant is a common English-language surname of Scottish origin, borne by numerous notable individuals across politics, arts, and public life.
E843097 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: Grant | Statement: [Miriam Grant, familyName, Grant]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Grant
Context triple: [Miriam Grant, familyName, Grant]
  • A. John
    John is the given name of John Henry Patterson, an American industrialist and founder of the National Cash Register Company.
  • B. John
    John B. Magruder was a Confederate major general during the American Civil War, known for his leadership in the Peninsula Campaign and his flamboyant personality.
  • C. John
    John is the given first name of Australian pathologist Robin Warren, who won the Nobel Prize for discovering the role of Helicobacter pylori in gastritis and peptic ulcers.
  • D. John
    John is the given first name of the individual known as Jake Eberts, a prominent Canadian film producer and financier.
  • E. John
    John Litel was an American character actor known for his prolific work in films and early television from the 1930s through the 1960s.
  • 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: Grant
Triple: [Miriam Grant, familyName, Grant]
Generated description
Grant is a common English-language surname of Scottish origin, borne by numerous notable individuals across politics, arts, and public life.
NED2 Entity disambiguation (via description) gpt-5-mini-2025-08-07
Target entity: Grant
Target entity description: Grant is a common English-language surname of Scottish origin, borne by numerous notable individuals across politics, arts, and public life.
  • A. Grant
    Grant is a masculine given name of English origin that is commonly used in the United States and other English-speaking countries.
  • B. Grant
    Grant is a publishing company best known for releasing special and limited editions of Stephen King’s works, including volumes in The Dark Tower series.
  • C. Grant chosen
    Grant is a common English-language surname of Scottish origin, borne by numerous notable figures in fields such as politics, entertainment, and sports.
  • D. Grant
    Grant is a fictional character portrayed by Canadian actor Justin Chatwin in film or television.
  • E. Grant
    Grant is the Rock-type Gym Leader of Cyllage City in the Kalos region in the Pokémon series.
  • F. None of above.

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_69e0b51ad810819098c12392c8e55f6c completed April 16, 2026, 10:08 a.m.
NER Named-entity recognition batch_69e77ecf12248190bb4172ad7416775e completed April 21, 2026, 1:42 p.m.
NED1 Entity disambiguation (via context triple) batch_6a099edfe15c8190bd52334727acd245 completed May 17, 2026, 10:56 a.m.
NEDg Description generation batch_6a099f69f1e08190bf96197fcf42b897 completed May 17, 2026, 10:58 a.m.
NED2 Entity disambiguation (via description) batch_6a099feeda3481909d8020763f32d430 completed May 17, 2026, 11:01 a.m.
Created at: April 16, 2026, 4:38 p.m.