Triple

T5803323
Position Surface form Disambiguated ID Type / Status
Subject National Theatre, London E128679 entity
Predicate architect P184 FINISHED
Object Peter Softley
Peter Softley is an architect best known for his work on the design of the National Theatre in London.
 E548543 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: Peter Softley | Statement: [National Theatre, London, architect, Peter Softley]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07 
Target entity: Peter Softley
Context triple: [National Theatre, London, architect, Peter Softley]
  • A. Peter Blaker
    Peter Blaker was a British Conservative politician who served in several ministerial roles, particularly in defense and foreign affairs, during the 1970s and early 1980s.
  • B. Paul Milner
    Paul Milner is a fictional World War II-era police sergeant and close colleague of Detective Chief Inspector Christopher Foyle in the British television series "Foyle's War."
  • C. Paul Snodgrass
    Paul Snodgrass is a South African comedian, radio personality, and writer known for his stand-up performances and work in local media.
  • D. Peter Snodgrass
    Peter Snodgrass was a 19th-century Australian pastoralist and politician who served in the Victorian Legislative Council and Assembly.
  • E. Peter Pugh
    Peter Pugh is a British author and publisher best known for writing corporate and business histories, including works on major companies and institutions.
  • 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: Peter Softley
Triple: [National Theatre, London, architect, Peter Softley]
Generated description
Peter Softley is an architect best known for his work on the design of the National Theatre in London.
NED2 Entity disambiguation (via description) gpt-5-mini-2025-08-07 
Target entity: Peter Softley
Target entity description: Peter Softley is an architect best known for his work on the design of the National Theatre in London.
  • A. Peter Blaker
    Peter Blaker was a British Conservative politician who served in several ministerial roles, particularly in defense and foreign affairs, during the 1970s and early 1980s.
  • B. Paul Milner
    Paul Milner is a fictional World War II-era police sergeant and close colleague of Detective Chief Inspector Christopher Foyle in the British television series "Foyle's War."
  • C. Paul Snodgrass
    Paul Snodgrass is a South African comedian, radio personality, and writer known for his stand-up performances and work in local media.
  • D. Peter Snodgrass
    Peter Snodgrass was a 19th-century Australian pastoralist and politician who served in the Victorian Legislative Council and Assembly.
  • E. Peter Pugh
    Peter Pugh is a British author and publisher best known for writing corporate and business histories, including works on major companies and institutions.
  • 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_69c00846a0d881909e46841f8e156b64 completed March 22, 2026, 3:18 p.m.
NER Named-entity recognition batch_69c02ad11cf0819094d8f9e4aaf099a2 completed March 22, 2026, 5:45 p.m.
NED1 Entity disambiguation (via context triple) batch_69c09833017c81908da09127e8455cb6 completed March 23, 2026, 1:32 a.m.
NEDg Description generation batch_69c09a38077081909873a9f43f578d36 completed March 23, 2026, 1:41 a.m.
NED2 Entity disambiguation (via description) batch_69c09aad318c81909420fa544676ce72 completed March 23, 2026, 1:43 a.m.
Created at: March 22, 2026, 3:52 p.m.