Triple

T15554700
Position Surface form Disambiguated ID Type / Status
Subject Goiás E370836 entity
Predicate ISOCode P208 FINISHED
Object BR-GO
BR-GO is the ISO 3166-2 code that identifies the Brazilian state of Goiás.
 E1163946 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-GO | Statement: [Goiás, ISOCode, BR-GO]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07 
Target entity: BR-GO
Context triple: [Goiás, ISOCode, BR-GO]
  • A. BR-SE
    BR-SE is the ISO 3166-2 code representing the Brazilian state of Sergipe.
  • B. Bento Gonçalves, Brazil
    Bento Gonçalves is a city in Brazil’s southern state of Rio Grande do Sul, known for its Italian heritage and as a major center of the country’s wine production.
  • C. Avaré
    Avaré is a municipality in the interior of Brazil known for its agricultural activities and proximity to the Jurumirim Reservoir, located in the state of São Paulo.
  • D. Parád
    Parád is a village and popular spa resort in northern Hungary, known for its mineral springs and scenic Mátra mountain surroundings.
  • E. Chiado
    Chiado is a historic and upscale neighborhood in central Lisbon known for its elegant shops, cafés, theaters, and literary heritage.
  • 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-GO
Triple: [Goiás, ISOCode, BR-GO]
Generated description
BR-GO is the ISO 3166-2 code that identifies the Brazilian state of Goiás.
NED2 Entity disambiguation (via description) gpt-5-mini-2025-08-07 
Target entity: BR-GO
Target entity description: BR-GO is the ISO 3166-2 code that identifies the Brazilian state of Goiás.
  • A. BR-SE
    BR-SE is the ISO 3166-2 code representing the Brazilian state of Sergipe.
  • B. Bento Gonçalves, Brazil
    Bento Gonçalves is a city in Brazil’s southern state of Rio Grande do Sul, known for its Italian heritage and as a major center of the country’s wine production.
  • C. Avaré
    Avaré is a municipality in the interior of Brazil known for its agricultural activities and proximity to the Jurumirim Reservoir, located in the state of São Paulo.
  • D. Parád
    Parád is a village and popular spa resort in northern Hungary, known for its mineral springs and scenic Mátra mountain surroundings.
  • E. Chiado
    Chiado is a historic and upscale neighborhood in central Lisbon known for its elegant shops, cafés, theaters, and literary heritage.
  • 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_69d85cc6cf40819091f4a5facee1ebe6 completed April 10, 2026, 2:13 a.m.
NER Named-entity recognition batch_69e04a96c0c88190808f68601a36b506 completed April 16, 2026, 2:33 a.m.
NED1 Entity disambiguation (via context triple) batch_69ff456209288190aba6debd434af741 completed May 9, 2026, 2:32 p.m.
NEDg Description generation batch_69ff471cb68c8190924e894b190f15f4 completed May 9, 2026, 2:39 p.m.
NED2 Entity disambiguation (via description) batch_69ff47aeddac8190a87024019ecb1396 completed May 9, 2026, 2:41 p.m.
Created at: April 10, 2026, 4:09 a.m.