Triple

T704118
Position Surface form Disambiguated ID Type / Status
Subject The Coca-Cola Company E14062 entity
Predicate tickerSymbol P1447 FINISHED
Object KO
KO is the New York Stock Exchange ticker symbol for The Coca-Cola Company, one of the world’s largest and most recognizable beverage corporations.
 E85131 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: KO | Statement: [The Coca-Cola Company, tickerSymbol, KO]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07 
Target entity: KO
Context triple: [The Coca-Cola Company, tickerSymbol, KO]
  • A. KE
    KE is the two-letter ISO 3166-1 alpha-2 country code assigned to Kenya for international identification and data standards.
  • B. KI
    KI is the abbreviation for the Karolinska Institute, a renowned Swedish medical university known for its leading research and role in selecting Nobel laureates in Physiology or Medicine.
  • C. KC
    KC is a common shorthand nickname for Kansas City, Missouri, a major Midwestern U.S. city known for its jazz heritage, barbecue, and sports teams.
  • D. KP
    KP is the commonly used abbreviation for Khyber Pakhtunkhwa, a province in northwestern Pakistan known for its mountainous terrain and diverse ethnic communities.
  • E. SK
    SK is the postcode area covering Stockport and surrounding parts of Greater Manchester and nearby counties in North West England.
  • 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: KO
Triple: [The Coca-Cola Company, tickerSymbol, KO]
Generated description
KO is the New York Stock Exchange ticker symbol for The Coca-Cola Company, one of the world’s largest and most recognizable beverage corporations.
NED2 Entity disambiguation (via description) gpt-5-mini-2025-08-07 
Target entity: KO
Target entity description: KO is the New York Stock Exchange ticker symbol for The Coca-Cola Company, one of the world’s largest and most recognizable beverage corporations.
  • A. KE
    KE is the two-letter ISO 3166-1 alpha-2 country code assigned to Kenya for international identification and data standards.
  • B. KI
    KI is the abbreviation for the Karolinska Institute, a renowned Swedish medical university known for its leading research and role in selecting Nobel laureates in Physiology or Medicine.
  • C. KC
    KC is a common shorthand nickname for Kansas City, Missouri, a major Midwestern U.S. city known for its jazz heritage, barbecue, and sports teams.
  • D. KP
    KP is the commonly used abbreviation for Khyber Pakhtunkhwa, a province in northwestern Pakistan known for its mountainous terrain and diverse ethnic communities.
  • E. SK
    SK is the postcode area covering Stockport and surrounding parts of Greater Manchester and nearby counties in North West England.
  • 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_69a493494ec48190ae6751683625a9ba completed March 1, 2026, 7:28 p.m.
NER Named-entity recognition batch_69a4a533fa788190bba0f55655469c46 completed March 1, 2026, 8:44 p.m.
NED1 Entity disambiguation (via context triple) batch_69a5dcae2ef88190a9ea1604429f048a completed March 2, 2026, 6:53 p.m.
NEDg Description generation batch_69a5df14e1788190bb2f2cc87cadcb40 completed March 2, 2026, 7:03 p.m.
NED2 Entity disambiguation (via description) batch_69a5ff5dd4808190bb8ae25fbdca0075 completed March 2, 2026, 9:21 p.m.
Created at: March 1, 2026, 7:36 p.m.