Triple

T3187912
Position Surface form Disambiguated ID Type / Status
Subject Central African Republic E66746 entity
Predicate ISO3166-1Alpha2 P189 FINISHED
Object CF
CF is the two-letter ISO 3166-1 alpha-2 country code assigned to the Central African Republic.
E336388 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: CF | Statement: [Central African Republic, ISO3166-1Alpha2, CF]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: CF
Context triple: [Central African Republic, ISO3166-1Alpha2, CF]
  • A. CF
    CF is the abbreviation for the Commonwealth Foundation, an intergovernmental organization that supports civil society and promotes democracy and development across the Commonwealth.
  • B. CF
    CF is a UK postcode area covering Cardiff and surrounding parts of South Wales, including the Vale of Glamorgan.
  • C. FC
    FC is the standard abbreviation for Fibre Channel, a high-speed network technology primarily used to connect computer data storage in storage area networks.
  • D. CAF
    CAF is the commonly used acronym for the Canadian Armed Forces, the unified military organization responsible for defending Canada and supporting international peace and security operations.
  • E. CAF
    CAF is a Spanish multinational company that designs and manufactures railway vehicles and related transport equipment used by metro systems worldwide.
  • 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: CF
Triple: [Central African Republic, ISO3166-1Alpha2, CF]
Generated description
CF is the two-letter ISO 3166-1 alpha-2 country code assigned to the Central African Republic.
NED2 Entity disambiguation (via description) gpt-5-mini-2025-08-07
Target entity: CF
Target entity description: CF is the two-letter ISO 3166-1 alpha-2 country code assigned to the Central African Republic.
  • A. CF
    CF is the abbreviation for the Commonwealth Foundation, an intergovernmental organization that supports civil society and promotes democracy and development across the Commonwealth.
  • B. CF
    CF is a UK postcode area covering Cardiff and surrounding parts of South Wales, including the Vale of Glamorgan.
  • C. FC
    FC is the standard abbreviation for Fibre Channel, a high-speed network technology primarily used to connect computer data storage in storage area networks.
  • D. CAF
    CAF is the commonly used acronym for the Canadian Armed Forces, the unified military organization responsible for defending Canada and supporting international peace and security operations.
  • E. CAF
    CAF is an abbreviation that can refer to various organizations or groups, most notably the Cactus Air Force, a World War II Allied air unit based on Guadalcanal.
  • 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_69ad8587c1bc8190a2595f2c22ee1001 completed March 8, 2026, 2:19 p.m.
NER Named-entity recognition batch_69ada6e279288190843837751e852c9e completed March 8, 2026, 4:42 p.m.
NED1 Entity disambiguation (via context triple) batch_69b24b8c075881909152ddca48b7da60 completed March 12, 2026, 5:13 a.m.
NEDg Description generation batch_69b24f86acf081909688c73b15c15383 completed March 12, 2026, 5:30 a.m.
NED2 Entity disambiguation (via description) batch_69b2501533008190bf178e3d11e2bea8 completed March 12, 2026, 5:33 a.m.
Created at: March 8, 2026, 3:06 p.m.