Triple

T1210469
Position Surface form Disambiguated ID Type / Status
Subject Sergipe E25986 entity
Predicate hasISOCode P189 FINISHED
Object BR-SE
BR-SE is the ISO 3166-2 code representing the Brazilian state of Sergipe.
 E137437 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: BR-SE | Statement: [Sergipe, hasISOCode, BR-SE]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07 
Target entity: BR-SE
Context triple: [Sergipe, hasISOCode, BR-SE]
  • A. BR2
    BR2 is a UK postcode district covering parts of Hayes and surrounding areas in the London Borough of Bromley in southeast England.
  • B. BR
    BR is the two-letter ISO 3166-1 alpha-2 country code that uniquely identifies Brazil in international standards and systems.
  • C. BR
    BR is the upper house of Austria’s parliament, representing the federal states in the legislative process.
  • D. Brazil
    Brazil is the largest country in South America, known for its vast Amazon rainforest, diverse culture, and major cities like São Paulo and Rio de Janeiro.
  • E. Brazil
    Brazil is a 1985 dystopian science fiction film known for its darkly satirical portrayal of a bureaucratic, totalitarian society and its distinctive, surreal visual style.
  • 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: BR-SE
Triple: [Sergipe, hasISOCode, BR-SE]
Generated description
BR-SE is the ISO 3166-2 code representing the Brazilian state of Sergipe.
NED2 Entity disambiguation (via description) gpt-5-mini-2025-08-07 
Target entity: BR-SE
Target entity description: BR-SE is the ISO 3166-2 code representing the Brazilian state of Sergipe.
  • A. BR2
    BR2 is a UK postcode district covering parts of Hayes and surrounding areas in the London Borough of Bromley in southeast England.
  • B. BR
    BR is the two-letter ISO 3166-1 alpha-2 country code that uniquely identifies Brazil in international standards and systems.
  • C. BR
    BR is the upper house of Austria’s parliament, representing the federal states in the legislative process.
  • D. Brazil
    Brazil is the largest country in South America, known for its vast Amazon rainforest, diverse culture, and major cities like São Paulo and Rio de Janeiro.
  • E. Brazil
    Brazil is a 1985 dystopian science fiction film known for its darkly satirical portrayal of a bureaucratic, totalitarian society and its distinctive, surreal visual style.
  • 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_69a4942b30f08190a91c60573e16b5ef completed March 1, 2026, 7:31 p.m.
NER Named-entity recognition batch_69a4bde4670481908c16a3a8c1a54aad completed March 1, 2026, 10:29 p.m.
NED1 Entity disambiguation (via context triple) batch_69ac7f43a12c8190a1ba90eefafd6bbc completed March 7, 2026, 7:40 p.m.
NEDg Description generation batch_69ac7fbadd08819090ef4a9aff3bef0b completed March 7, 2026, 7:42 p.m.
NED2 Entity disambiguation (via description) batch_69ac8022a6b08190ba6a1448cebe6017 completed March 7, 2026, 7:44 p.m.
Created at: March 1, 2026, 7:46 p.m.