Triple

T10115657
Position Surface form Disambiguated ID Type / Status
Subject Ratcliffe E218349 entity
Predicate hasNotableBearer P458 FINISHED
Object Michael Ratcliffe
Michael Ratcliffe is a relatively obscure individual whose primary distinguishing feature is sharing the Ratcliffe surname, with no widely documented public achievements or roles.
E854761 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 Ratcliffe | Statement: [Ratcliffe, hasNotableBearer, Michael Ratcliffe]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Michael Ratcliffe
Context triple: [Ratcliffe, hasNotableBearer, Michael Ratcliffe]
  • A. Ian Roberts
    Ian Roberts is a South African actor best known for his roles in film, television, and stage productions, often portraying rugged or authoritative characters.
  • B. Stephen Pycroft
    Stephen Pycroft is a British businessman best known as the founder of the construction and consultancy company Mace Group.
  • C. Jeffrey Stott
    Jeffrey Stott is a film producer best known for his work on the political comedy film "The American President."
  • D. Jonathan Roberts
    Jonathan Roberts is an American screenwriter best known for co-writing Disney’s animated classic "The Lion King."
  • E. Jonathan Roberts
    Jonathan Roberts is a creator known for his work on the project or character "Scar."
  • 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 Ratcliffe
Triple: [Ratcliffe, hasNotableBearer, Michael Ratcliffe]
Generated description
Michael Ratcliffe is a relatively obscure individual whose primary distinguishing feature is sharing the Ratcliffe surname, with no widely documented public achievements or roles.
NED2 Entity disambiguation (via description) gpt-5-mini-2025-08-07
Target entity: Michael Ratcliffe
Target entity description: Michael Ratcliffe is a relatively obscure individual whose primary distinguishing feature is sharing the Ratcliffe surname, with no widely documented public achievements or roles.
  • A. Ian Roberts
    Ian Roberts is a South African actor best known for his roles in film, television, and stage productions, often portraying rugged or authoritative characters.
  • B. Stephen Pycroft
    Stephen Pycroft is a British businessman best known as the founder of the construction and consultancy company Mace Group.
  • C. Jeffrey Stott
    Jeffrey Stott is a film producer best known for his work on the political comedy film "The American President."
  • D. Jonathan Roberts
    Jonathan Roberts is an American screenwriter best known for co-writing Disney’s animated classic "The Lion King."
  • E. Jonathan Roberts
    Jonathan Roberts is a creator known for his work on the project or character "Scar."
  • 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_69ca83da93fc8190b54e44bc2b34857c completed March 30, 2026, 2:08 p.m.
NER Named-entity recognition batch_69cdd161831c81908bb3c77caa7c3ce1 completed April 2, 2026, 2:16 a.m.
NED1 Entity disambiguation (via context triple) batch_69d71c559910819092b0eae9c05aa7dc completed April 9, 2026, 3:26 a.m.
NEDg Description generation batch_69d73180d90481908f1b4768230edd36 completed April 9, 2026, 4:56 a.m.
NED2 Entity disambiguation (via description) batch_69d7326b14988190bff33dc01e690707 completed April 9, 2026, 5 a.m.
Created at: March 30, 2026, 9:04 p.m.