Triple

T5098323
Position Surface form Disambiguated ID Type / Status
Subject Alan Gilbert E114920 entity
Predicate hasRelative P367 FINISHED
Object Michael Gilbert
Michael Gilbert is a member of the Gilbert family, related to the American conductor Alan Gilbert.
E494810 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: Michael Gilbert | Statement: [Alan Gilbert, hasRelative, Michael Gilbert]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Michael Gilbert
Context triple: [Alan Gilbert, hasRelative, Michael Gilbert]
  • A. Laurence Gardner
    Laurence Gardner was a British author and lecturer known for his controversial books on alternative history, secret societies, and speculative theories about royal bloodlines and religious history.
  • B. Clifford May
    Clifford May is an American journalist and foreign policy analyst best known as the founder and president of the Foundation for Defense of Democracies.
  • C. Jeffrey Archer
    Jeffrey Archer is a British author and former politician best known for his bestselling novels and thrillers.
  • D. Len Deighton
    Len Deighton is a British author and historian best known for his spy novels, including "The IPCRESS File," and his influential works on military history.
  • E. John Robie
    John Robie is a retired jewel thief known as "The Cat" who becomes embroiled in a new string of robberies on the French Riviera in Alfred Hitchcock's film "To Catch a Thief."
  • 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: Michael Gilbert
Triple: [Alan Gilbert, hasRelative, Michael Gilbert]
Generated description
Michael Gilbert is a member of the Gilbert family, related to the American conductor Alan Gilbert.
NED2 Entity disambiguation (via description) gpt-5-mini-2025-08-07
Target entity: Michael Gilbert
Target entity description: Michael Gilbert is a member of the Gilbert family, related to the American conductor Alan Gilbert.
  • A. Laurence Gardner
    Laurence Gardner was a British author and lecturer known for his controversial books on alternative history, secret societies, and speculative theories about royal bloodlines and religious history.
  • B. Clifford May
    Clifford May is an American journalist and foreign policy analyst best known as the founder and president of the Foundation for Defense of Democracies.
  • C. Jeffrey Archer
    Jeffrey Archer is a British author and former politician best known for his bestselling novels and thrillers.
  • D. Len Deighton
    Len Deighton is a British author and historian best known for his spy novels, including "The IPCRESS File," and his influential works on military history.
  • E. John Robie
    John Robie is a retired jewel thief known as "The Cat" who becomes embroiled in a new string of robberies on the French Riviera in Alfred Hitchcock's film "To Catch a Thief."
  • 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_69bd443fc49c819089629c00e311310c completed March 20, 2026, 12:57 p.m.
NER Named-entity recognition batch_69bd7567d21081909227ed8f08b74c71 completed March 20, 2026, 4:27 p.m.
NED1 Entity disambiguation (via context triple) batch_69beba8529ec8190bb1e97eb1044c899 completed March 21, 2026, 3:34 p.m.
NEDg Description generation batch_69bebc65f37c819088077a02c5a2939e completed March 21, 2026, 3:42 p.m.
NED2 Entity disambiguation (via description) batch_69bebcc8ad2481909ec38247b32dfdb0 completed March 21, 2026, 3:44 p.m.
Created at: March 20, 2026, 1:40 p.m.