Triple

T20946957
Position Surface form Disambiguated ID Type / Status
Subject Barreiro E515866 entity
Predicate hasISO3166-1Alpha2Code P19525 FINISHED
Object CV
CV is the ISO 3166-1 alpha-2 country code for Cape Verde, an island nation off the west coast of Africa.
 E1325323 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: CV | Statement: [Barreiro, hasISO3166-1Alpha2Code, CV]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07 
Target entity: CV
Context triple: [Barreiro, hasISO3166-1Alpha2Code, CV]
  • A. CV
    CV is a common abbreviation for Chula Vista, a coastal city in Southern California located just south of San Diego.
  • B. CV
    CV is the standard abbreviation for the Central Vermont Railway, a historic regional railroad that operated primarily in Vermont and neighboring areas.
  • C. CV
    CV is the ISO 3166-1 alpha-2 country code for Cape Verde, an island nation off the west coast of Africa.
  • D. CV
    CV is the frequent flyer program of Vistara, a full-service Indian airline jointly owned by Tata Sons and Singapore Airlines.
  • E. CV
    CV is the post-nominal abbreviation used to denote recipients of the Cross of Valour, a high-level decoration for extraordinary bravery.
  • 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: CV
Triple: [Barreiro, hasISO3166-1Alpha2Code, CV]
Generated description
CV is the ISO 3166-1 alpha-2 country code for Cape Verde, an island nation off the west coast of Africa.
NED2 Entity disambiguation (via description) gpt-5-mini-2025-08-07 
Target entity: CV
Target entity description: CV is the ISO 3166-1 alpha-2 country code for Cape Verde, an island nation off the west coast of Africa.
  • A. CV
    CV is a common abbreviation for Chula Vista, a coastal city in Southern California located just south of San Diego.
  • B. CV
    CV is the standard abbreviation for the Central Vermont Railway, a historic regional railroad that operated primarily in Vermont and neighboring areas.
  • C. CV
    CV is the post-nominal abbreviation used to denote recipients of the Cross of Valour, a high-level decoration for extraordinary bravery.
  • D. CV chosen
    CV is the ISO 3166-1 alpha-2 country code for Cape Verde, an island nation off the west coast of Africa.
  • E. CV
    CV is the frequent flyer program of Vistara, a full-service Indian airline jointly owned by Tata Sons and Singapore Airlines.
  • 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_69e0b4fcd678819087a304291f14330a completed April 16, 2026, 10:07 a.m.
NER Named-entity recognition batch_69e6fad97aa48190b4be692e3afce8c9 completed April 21, 2026, 4:19 a.m.
NED1 Entity disambiguation (via context triple) batch_6a09278afe48819093d5ed09a15df594 completed May 17, 2026, 2:27 a.m.
NEDg Description generation batch_6a092849ffcc8190acd608b30edcf5d1 completed May 17, 2026, 2:30 a.m.
NED2 Entity disambiguation (via description) batch_6a0929485ebc8190ab8bc316b3e802ca completed May 17, 2026, 2:34 a.m.
Created at: April 16, 2026, 12:56 p.m.