Triple

T14765696
Position Surface form Disambiguated ID Type / Status
Subject Francesca Nora Bateman E346987 entity
Predicate familyName P18 FINISHED
Object Bateman
Bateman is a surname of English origin borne by various notable individuals in fields such as acting, sports, and politics.
 E1119334 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: Bateman | Statement: [Francesca Nora Bateman, familyName, Bateman]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07 
Target entity: Bateman
Context triple: [Francesca Nora Bateman, familyName, Bateman]
  • A. Bateman's
    Bateman's is a 17th-century sandstone house in East Sussex, England, best known as the former home of author Rudyard Kipling and now preserved by the National Trust.
  • B. Beatson
    Beatson is an alternative spelling or variant form of the surname Bateson.
  • C. Beyton
    Beyton is a small rural village and civil parish in the English county of Suffolk, known for its traditional village green and historic buildings.
  • D. Bennett
    Bennett is a common English-language surname of Anglo-Norman origin borne by numerous notable individuals across politics, arts, and sciences.
  • E. Bennett
    Bennett is the main villain and former comrade-turned-mercenary antagonist who battles Arnold Schwarzenegger’s character in the 1985 action film "Commando."
  • 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: Bateman
Triple: [Francesca Nora Bateman, familyName, Bateman]
Generated description
Bateman is a surname of English origin borne by various notable individuals in fields such as acting, sports, and politics.
NED2 Entity disambiguation (via description) gpt-5-mini-2025-08-07 
Target entity: Bateman
Target entity description: Bateman is a surname of English origin borne by various notable individuals in fields such as acting, sports, and politics.
  • A. Bateman's
    Bateman's is a 17th-century sandstone house in East Sussex, England, best known as the former home of author Rudyard Kipling and now preserved by the National Trust.
  • B. Beatson
    Beatson is an alternative spelling or variant form of the surname Bateson.
  • C. Beyton
    Beyton is a small rural village and civil parish in the English county of Suffolk, known for its traditional village green and historic buildings.
  • D. Bennett
    Bennett is a common English-language surname of Anglo-Norman origin borne by numerous notable individuals across politics, arts, and sciences.
  • E. Bennett
    Bennett is the main villain and former comrade-turned-mercenary antagonist who battles Arnold Schwarzenegger’s character in the 1985 action film "Commando."
  • 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_69d822e8896c819091169882f9b20486 completed April 9, 2026, 10:06 p.m.
NER Named-entity recognition batch_69dec7f576c881909da70627f5897c94 completed April 14, 2026, 11:04 p.m.
NED1 Entity disambiguation (via context triple) batch_69fe0cf4cef081909fa62125f43b36bc completed May 8, 2026, 4:19 p.m.
NEDg Description generation batch_69fe1d66af94819091a84c2225cc7828 completed May 8, 2026, 5:29 p.m.
NED2 Entity disambiguation (via description) batch_69fe1e0089e08190a91f8683e683c371 completed May 8, 2026, 5:31 p.m.
Created at: April 10, 2026, 1:30 a.m.