Triple

T10223749
Position Surface form Disambiguated ID Type / Status
Subject Orlando Figes E242646 entity
Predicate familyName P18 FINISHED
Object Figes
Figes is a surname most notably associated with British historian and author Orlando Figes, known for his works on Russian and European history.
 E850550 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: Figes | Statement: [Orlando Figes, familyName, Figes]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07 
Target entity: Figes
Context triple: [Orlando Figes, familyName, Figes]
  • A. Faulks
    Faulks is the surname of British novelist and journalist Sebastian Faulks, best known for his historical and literary fiction.
  • B. Hettie
    Hettie is a feminine given name, commonly used as a diminutive or nickname for Heather and similar names.
  • C. Gies
    Gies is the surname of Miep Gies, the Dutch woman renowned for helping hide Anne Frank and preserving her diary during World War II.
  • D. Schiffrin
    Schiffrin is a surname most notably associated with André Schiffrin, an influential publisher and intellectual known for his work in progressive and independent publishing.
  • E. Logue
    Logue is a surname most notably associated with Lionel Logue, the Australian speech therapist who helped King George VI overcome his stammer.
  • 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: Figes
Triple: [Orlando Figes, familyName, Figes]
Generated description
Figes is a surname most notably associated with British historian and author Orlando Figes, known for his works on Russian and European history.
NED2 Entity disambiguation (via description) gpt-5-mini-2025-08-07 
Target entity: Figes
Target entity description: Figes is a surname most notably associated with British historian and author Orlando Figes, known for his works on Russian and European history.
  • A. Faulks
    Faulks is the surname of British novelist and journalist Sebastian Faulks, best known for his historical and literary fiction.
  • B. Hettie
    Hettie is a feminine given name, commonly used as a diminutive or nickname for Heather and similar names.
  • C. Gies
    Gies is the surname of Miep Gies, the Dutch woman renowned for helping hide Anne Frank and preserving her diary during World War II.
  • D. Schiffrin
    Schiffrin is a surname most notably associated with André Schiffrin, an influential publisher and intellectual known for his work in progressive and independent publishing.
  • E. Logue
    Logue is a surname most notably associated with Lionel Logue, the Australian speech therapist who helped King George VI overcome his stammer.
  • 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_69d381ae26c48190985abd0e25ee5d04 completed April 6, 2026, 9:49 a.m.
NER Named-entity recognition batch_69d3aa84a9ac819093d551005a1c8f3d completed April 6, 2026, 12:43 p.m.
NED1 Entity disambiguation (via context triple) batch_69d6a8457e9c819085f222bb002be892 completed April 8, 2026, 7:11 p.m.
NEDg Description generation batch_69d6d00220ec81909d189e64eda2a28f completed April 8, 2026, 10 p.m.
NED2 Entity disambiguation (via description) batch_69d6df44ad5481909100b596d2bf3b07 completed April 8, 2026, 11:05 p.m.
Created at: April 6, 2026, 11:11 a.m.