Triple

T16891494
Position Surface form Disambiguated ID Type / Status
Subject XIII Olympic Winter Games E424183 entity
Predicate torchLighter P12120 FINISHED
Object Charles Kerr
Charles Kerr is an athlete best known for lighting the Olympic cauldron at the XIII Olympic Winter Games.
 E424188 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: Charles Kerr | Statement: [XIII Olympic Winter Games, torchLighter, Charles Kerr]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07 
Target entity: Charles Kerr
Context triple: [XIII Olympic Winter Games, torchLighter, Charles Kerr]
  • A. Charles Kerr
    Charles Kerr is an athlete best known for lighting the Olympic cauldron at the 1980 Winter Olympics in Lake Placid.
  • B. William Kerr
    William Kerr is a film editor known for his work on major Hollywood comedies, including "The Five-Year Engagement."
  • C. William Kerr
    William Kerr was a Scottish gardener and plant collector for the Royal Botanic Gardens, Kew, known for introducing numerous Asian plant species to Europe.
  • D. William McGregor
    William McGregor was a Scottish football administrator best known for initiating and organizing the creation of the English Football League in 1888.
  • E. Charles Alling Gifford
    Charles Alling Gifford was an American architect known for designing prominent early 20th-century resort hotels and other large-scale buildings in the United States.
  • 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: Charles Kerr
Triple: [XIII Olympic Winter Games, torchLighter, Charles Kerr]
Generated description
Charles Kerr is an athlete best known for lighting the Olympic cauldron at the XIII Olympic Winter Games.
NED2 Entity disambiguation (via description) gpt-5-mini-2025-08-07 
Target entity: Charles Kerr
Target entity description: Charles Kerr is an athlete best known for lighting the Olympic cauldron at the XIII Olympic Winter Games.
  • A. Charles Kerr chosen
    Charles Kerr is an athlete best known for lighting the Olympic cauldron at the 1980 Winter Olympics in Lake Placid.
  • B. William Kerr
    William Kerr is a film editor known for his work on major Hollywood comedies, including "The Five-Year Engagement."
  • C. William Kerr
    William Kerr was a Scottish gardener and plant collector for the Royal Botanic Gardens, Kew, known for introducing numerous Asian plant species to Europe.
  • D. William McGregor
    William McGregor was a Scottish football administrator best known for initiating and organizing the creation of the English Football League in 1888.
  • E. Charles Alling Gifford
    Charles Alling Gifford was an American architect known for designing prominent early 20th-century resort hotels and other large-scale buildings in the United States.
  • F. None of above.

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_69d889da3e8c8190a2b118f383f0beac completed April 10, 2026, 5:25 a.m.
NER Named-entity recognition batch_69e3bbc5a5308190937ebd05356bd91d completed April 18, 2026, 5:13 p.m.
NED1 Entity disambiguation (via context triple) batch_6a00c2c1eee48190bc906e658d7729a4 completed May 10, 2026, 5:39 p.m.
NEDg Description generation batch_6a00c3b4a36c8190804b8616958002fc completed May 10, 2026, 5:43 p.m.
NED2 Entity disambiguation (via description) batch_6a00c434d8f88190a71c1c4c8e475e33 completed May 10, 2026, 5:45 p.m.
Created at: April 10, 2026, 5:29 a.m.