Triple

T37579278
Position Surface form Disambiguated ID Type / Status
Subject Chief Executive Officer of The Coca-Cola Company E934910 entity
Predicate headquartersCityOfEmployer P60125 FINISHED
Object Atlanta, Georgia NE NERFINISHED

How this triple was built (2 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: Atlanta, Georgia | Statement: [Chief Executive Officer of The Coca-Cola Company, headquartersCityOfEmployer, Atlanta, Georgia]
PD Predicate disambiguation gpt-5-mini-2025-08-07
Target predicate: headquartersCityOfEmployer
Context triple: [Chief Executive Officer of The Coca-Cola Company, headquartersCityOfEmployer, Atlanta, Georgia]
  • A. majorEmployerCity
    Indicates that a city is a primary or significant employer of a given entity (such as an organization or population).
  • B. hasHeadOfficeCity chosen
    Indicates that an organization’s main or central administrative office is located in a particular city.
  • C. employerHeadquarters
    Indicates the location where an employer’s main corporate offices or central administrative operations are based.
  • D. laterCompanyHeadquartersCity
    Indicates that the specified city is the location of a company’s headquarters during a later period in time, following an earlier headquarters location.
  • E. headquartersMetroArea
    Indicates that an organization’s main headquarters is located within a specified metropolitan area.
  • F. None of above.

Provenance (3 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_69f76ecd99148190be327e391a70f5b6 completed May 3, 2026, 3:50 p.m.
NER Named-entity recognition batch_69fba61dff5081909fec88a7aeb0c8a1 completed May 6, 2026, 8:35 p.m.
PD Predicate disambiguation batch_69fba350e9a8819095893229d9643572 completed May 6, 2026, 8:23 p.m.
Created at: May 3, 2026, 4:17 p.m.