Triple

T7369360
Position Surface form Disambiguated ID Type / Status
Subject Pará E169954 entity
Predicate hasMajorCity P316 FINISHED
Object Marabá
Marabá is a major industrial and commercial city in southeastern Pará, Brazil, known for its role in mining, steel production, and as a regional transportation hub.
 E660114 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: Marabá | Statement: [Pará, hasMajorCity, Marabá]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07 
Target entity: Marabá
Context triple: [Pará, hasMajorCity, Marabá]
  • A. Arapiraca
    Arapiraca is a major city in the Brazilian state of Alagoas, known as an important regional commercial and agricultural center.
  • B. Panarima
    Panarima is a musical track featured on the album "Legend of the Sun Virgin."
  • C. Guajá
    Guajá is an indigenous language of the Tupi–Guaraní family spoken by the Guajá people of the Brazilian Amazon.
  • D. Pará
    Pará is a large state in northern Brazil known for its Amazon rainforest, rich biodiversity, and the major port city of Belém.
  • E. Barra de Mamanguape
    Barra de Mamanguape is a coastal area in the state of Paraíba, Brazil, known for its estuary, mangrove ecosystems, and protected marine environments that include manatee habitats.
  • 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: Marabá
Triple: [Pará, hasMajorCity, Marabá]
Generated description
Marabá is a major industrial and commercial city in southeastern Pará, Brazil, known for its role in mining, steel production, and as a regional transportation hub.
NED2 Entity disambiguation (via description) gpt-5-mini-2025-08-07 
Target entity: Marabá
Target entity description: Marabá is a major industrial and commercial city in southeastern Pará, Brazil, known for its role in mining, steel production, and as a regional transportation hub.
  • A. Arapiraca
    Arapiraca is a major city in the Brazilian state of Alagoas, known as an important regional commercial and agricultural center.
  • B. Panarima
    Panarima is a musical track featured on the album "Legend of the Sun Virgin."
  • C. Guajá
    Guajá is an indigenous language of the Tupi–Guaraní family spoken by the Guajá people of the Brazilian Amazon.
  • D. Pará
    Pará is a large state in northern Brazil known for its Amazon rainforest, rich biodiversity, and the major port city of Belém.
  • E. Barra de Mamanguape
    Barra de Mamanguape is a coastal area in the state of Paraíba, Brazil, known for its estuary, mangrove ecosystems, and protected marine environments that include manatee habitats.
  • 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_69c68a5ade988190885b7175f63b7534 completed March 27, 2026, 1:47 p.m.
NER Named-entity recognition batch_69c6f1810668819094aec4b237d08068 completed March 27, 2026, 9:07 p.m.
NED1 Entity disambiguation (via context triple) batch_69c802c3a4788190850294b054b9c928 completed March 28, 2026, 4:33 p.m.
NEDg Description generation batch_69c803baa4d48190941174246f533399 completed March 28, 2026, 4:37 p.m.
NED2 Entity disambiguation (via description) batch_69c80457cca08190a392b4efaa50a3f4 completed March 28, 2026, 4:39 p.m.
Created at: March 27, 2026, 3:07 p.m.