Triple

T330213
Position Surface form Disambiguated ID Type / Status
Subject Saudi Arabia E6608 entity
Predicate ISO3166-1Alpha2 P189 FINISHED
Object SA
SA is the two-letter ISO 3166-1 alpha-2 country code representing the Kingdom of Saudi Arabia.
 E42283 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: SA | Statement: [Saudi Arabia, ISO3166-1Alpha2, SA]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07 
Target entity: SA
Context triple: [Saudi Arabia, ISO3166-1Alpha2, SA]
  • A. SA
    The SA (Sturmabteilung) was the Nazi Party’s paramilitary organization known for its role in Adolf Hitler’s rise to power through intimidation, street violence, and mass rallies in early 20th-century Germany.
  • B. SA
    SA is a key 3GPP technical specification group responsible for defining the overall system architecture and service capabilities of mobile telecommunications networks.
  • C. GA
    GA is the commonly used abbreviation for the United Nations General Assembly, the main deliberative body of the UN where all member states are represented.
  • D. AL
    AL is the common abbreviation for the American League, one of the two major professional baseball leagues that make up Major League Baseball in the United States and Canada.
  • E. SAN
    SAN is the three-letter IATA airport code for San Diego International Airport, the primary commercial airport serving the San Diego, California area.
  • 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: SA
Triple: [Saudi Arabia, ISO3166-1Alpha2, SA]
Generated description
SA is the two-letter ISO 3166-1 alpha-2 country code representing the Kingdom of Saudi Arabia.
NED2 Entity disambiguation (via description) gpt-5-mini-2025-08-07 
Target entity: SA
Target entity description: SA is the two-letter ISO 3166-1 alpha-2 country code representing the Kingdom of Saudi Arabia.
  • A. SA
    The SA (Sturmabteilung) was the Nazi Party’s paramilitary organization known for its role in Adolf Hitler’s rise to power through intimidation, street violence, and mass rallies in early 20th-century Germany.
  • B. SA
    SA is a key 3GPP technical specification group responsible for defining the overall system architecture and service capabilities of mobile telecommunications networks.
  • C. GA
    GA is the commonly used abbreviation for the United Nations General Assembly, the main deliberative body of the UN where all member states are represented.
  • D. AL
    AL is the common abbreviation for the American League, one of the two major professional baseball leagues that make up Major League Baseball in the United States and Canada.
  • E. SAN
    SAN is the three-letter IATA airport code for San Diego International Airport, the primary commercial airport serving the San Diego, California area.
  • 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_69a2e79434908190a9d5afe415153ad9 completed Feb. 28, 2026, 1:03 p.m.
NER Named-entity recognition batch_69a2eaaeb64881909c7ab9bca3378e2b completed Feb. 28, 2026, 1:16 p.m.
NED1 Entity disambiguation (via context triple) batch_69a3cff160788190a49faad3c011965e completed March 1, 2026, 5:34 a.m.
NEDg Description generation batch_69a3d0dff47881909b2dc7002b16e1cd completed March 1, 2026, 5:38 a.m.
NED2 Entity disambiguation (via description) batch_69a3d15c60d4819091d615246267a2a7 completed March 1, 2026, 5:40 a.m.
Created at: Feb. 28, 2026, 1:08 p.m.