Triple

T645010
Position Surface form Disambiguated ID Type / Status
Subject 1948 Summer Olympics E11221 entity
Predicate cauldronLighter P12657 FINISHED
Object John Mark
John Mark was a British athlete best known for lighting the Olympic cauldron at the opening ceremony of the 1948 London Summer Olympics.
 E100681 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: John Mark | Statement: [1948 Summer Olympics, cauldronLighter, John Mark]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07 
Target entity: John Mark
Context triple: [1948 Summer Olympics, cauldronLighter, John Mark]
  • A. John Mark
    John Mark is a New Testament figure traditionally regarded as the author of the Gospel of Mark and a companion of the apostles Peter and Paul.
  • B. Michael J. Smith
    Michael J. Smith was a U.S. Navy captain and NASA astronaut who served as the pilot on the ill-fated Space Shuttle Challenger mission STS-51-L.
  • C. David Marks
    David Marks was a British architect best known as the co-designer of the London Eye and other major public structures.
  • D. Matthew Fuller
    Matthew Fuller is a descendant of filmmaker Samuel Fuller, known primarily in relation to his famous relative.
  • E. Christian Colson
    Christian Colson is a British film producer best known for his Academy Award-winning work on "Slumdog Millionaire" and other acclaimed dramas.
  • 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: John Mark
Triple: [1948 Summer Olympics, cauldronLighter, John Mark]
Generated description
John Mark was a British athlete best known for lighting the Olympic cauldron at the opening ceremony of the 1948 London Summer Olympics.
NED2 Entity disambiguation (via description) gpt-5-mini-2025-08-07 
Target entity: John Mark
Target entity description: John Mark was a British athlete best known for lighting the Olympic cauldron at the opening ceremony of the 1948 London Summer Olympics.
  • A. John Mark
    John Mark is a New Testament figure traditionally regarded as the author of the Gospel of Mark and a companion of the apostles Peter and Paul.
  • B. Michael J. Smith
    Michael J. Smith was a U.S. Navy captain and NASA astronaut who served as the pilot on the ill-fated Space Shuttle Challenger mission STS-51-L.
  • C. David Marks
    David Marks was a British architect best known as the co-designer of the London Eye and other major public structures.
  • D. Matthew Fuller
    Matthew Fuller is a descendant of filmmaker Samuel Fuller, known primarily in relation to his famous relative.
  • E. Christian Colson
    Christian Colson is a British film producer best known for his Academy Award-winning work on "Slumdog Millionaire" and other acclaimed dramas.
  • 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_69a493266a2881909daf4c40f719dee8 completed March 1, 2026, 7:27 p.m.
NER Named-entity recognition batch_69a49f19f9a08190b0bf6e19b32427ff completed March 1, 2026, 8:18 p.m.
NED1 Entity disambiguation (via context triple) batch_69a7927c75448190aafcaa955519833c completed March 4, 2026, 2:01 a.m.
NEDg Description generation batch_69a7965d1ce08190a1b6b30ffa23f974 completed March 4, 2026, 2:18 a.m.
NED2 Entity disambiguation (via description) batch_69a796b5cf708190ac3d11f80a3af7ce completed March 4, 2026, 2:19 a.m.
Created at: March 1, 2026, 7:36 p.m.