Triple

T3748893
Position Surface form Disambiguated ID Type / Status
Subject Henry Bartle Frere E81278 entity
Predicate familyName P18 FINISHED
Object Frere
Frere is an English surname most notably associated with Sir Henry Bartle Frere, a 19th-century British colonial administrator and diplomat.
 E383602 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: Frere | Statement: [Henry Bartle Frere, familyName, Frere]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07 
Target entity: Frere
Context triple: [Henry Bartle Frere, familyName, Frere]
  • A. Firmin
    Firmin is a French given name notably borne by Firmin Didot, a renowned printer, typefounder, and member of the influential Didot family in the history of typography.
  • B. Freuchie
    Freuchie is a small village in the Kingdom of Fife, Scotland, known for its rural character and historic cricket club.
  • C. Ganthier
    Ganthier is a commune in western Haiti known for its rural character and proximity to the capital, Port-au-Prince.
  • D. Greuze
    Greuze is a French surname most famously associated with Jean-Baptiste Greuze, an 18th-century painter known for his sentimental and moralizing genre scenes.
  • E. Bézu Fache
    Bézu Fache is the stern and devout captain of the French Judicial Police who leads the investigation at the Louvre in Dan Brown’s novel *The Da Vinci Code*.
  • 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: Frere
Triple: [Henry Bartle Frere, familyName, Frere]
Generated description
Frere is an English surname most notably associated with Sir Henry Bartle Frere, a 19th-century British colonial administrator and diplomat.
NED2 Entity disambiguation (via description) gpt-5-mini-2025-08-07 
Target entity: Frere
Target entity description: Frere is an English surname most notably associated with Sir Henry Bartle Frere, a 19th-century British colonial administrator and diplomat.
  • A. Firmin
    Firmin is a French given name notably borne by Firmin Didot, a renowned printer, typefounder, and member of the influential Didot family in the history of typography.
  • B. Freuchie
    Freuchie is a small village in the Kingdom of Fife, Scotland, known for its rural character and historic cricket club.
  • C. Ganthier
    Ganthier is a commune in western Haiti known for its rural character and proximity to the capital, Port-au-Prince.
  • D. Greuze
    Greuze is a French surname most famously associated with Jean-Baptiste Greuze, an 18th-century painter known for his sentimental and moralizing genre scenes.
  • E. Bézu Fache
    Bézu Fache is the stern and devout captain of the French Judicial Police who leads the investigation at the Louvre in Dan Brown’s novel *The Da Vinci Code*.
  • 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_69ad8b19b7b08190a6188804e99c53e9 completed March 8, 2026, 2:43 p.m.
NER Named-entity recognition batch_69adcb6bf95c81909796fbc84995ae05 completed March 8, 2026, 7:18 p.m.
NED1 Entity disambiguation (via context triple) batch_69b4db31f964819087bab143f638754f completed March 14, 2026, 3:51 a.m.
NEDg Description generation batch_69b4dbbc23f08190a03ef4e4197398a4 completed March 14, 2026, 3:53 a.m.
NED2 Entity disambiguation (via description) batch_69b4dcac6fdc81908998415ffe1aabaa completed March 14, 2026, 3:57 a.m.
Created at: March 8, 2026, 3:35 p.m.