Triple

T20916650
Position Surface form Disambiguated ID Type / Status
Subject Helena E515089 entity
Predicate mainCharacter P1183 FINISHED
Object Estácio
Estácio is a central character in Brazilian writer Machado de Assis’s novel "Helena," serving as one of the key figures through whom the story’s family drama and moral conflicts unfold.
 E1457640 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: Estácio | Statement: [Helena, mainCharacter, Estácio]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07 
Target entity: Estácio
Context triple: [Helena, mainCharacter, Estácio]
  • A. da Nóbrega
    da Nóbrega is the surname of Manuel da Nóbrega, a 16th-century Portuguese Jesuit priest known as a key founder and early leader of colonial Brazil’s Jesuit missions.
  • B. Gonçalves
    Gonçalves is a common Portuguese surname, especially prevalent in Portugal and Brazil, derived from the given name Gonçalo.
  • C. Werdenberg
    Werdenberg is a region in the Swiss canton of St. Gallen, known for its historic town and castle near the Rhine Valley.
  • D. Quixeramobim
    Quixeramobim is a municipality in northeastern Brazil known for its semi-arid landscape and agricultural activities within the state of Ceará.
  • E. Monteiro
    Monteiro is a Portuguese surname commonly borne by individuals of Lusophone origin.
  • 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: Estácio
Triple: [Helena, mainCharacter, Estácio]
Generated description
Estácio is a central character in Brazilian writer Machado de Assis’s novel "Helena," serving as one of the key figures through whom the story’s family drama and moral conflicts unfold.
NED2 Entity disambiguation (via description) gpt-5-mini-2025-08-07 
Target entity: Estácio
Target entity description: Estácio is a central character in Brazilian writer Machado de Assis’s novel "Helena," serving as one of the key figures through whom the story’s family drama and moral conflicts unfold.
  • A. da Nóbrega
    da Nóbrega is the surname of Manuel da Nóbrega, a 16th-century Portuguese Jesuit priest known as a key founder and early leader of colonial Brazil’s Jesuit missions.
  • B. Gonçalves
    Gonçalves is a common Portuguese surname, especially prevalent in Portugal and Brazil, derived from the given name Gonçalo.
  • C. Werdenberg
    Werdenberg is a region in the Swiss canton of St. Gallen, known for its historic town and castle near the Rhine Valley.
  • D. Quixeramobim
    Quixeramobim is a municipality in northeastern Brazil known for its semi-arid landscape and agricultural activities within the state of Ceará.
  • E. Monteiro
    Monteiro is a Portuguese surname commonly borne by individuals of Lusophone origin.
  • 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_69e0b4f9d5ec8190bb2bd27350ed341c completed April 16, 2026, 10:07 a.m.
NER Named-entity recognition batch_69e6ec635f4881909a560fb891100d8c completed April 21, 2026, 3:17 a.m.
NED1 Entity disambiguation (via context triple) batch_6a091fc4d81081908c412567cd0e5073 completed May 17, 2026, 1:54 a.m.
NEDg Description generation batch_6a09210bde4c8190841af0f9a29ecdd9 completed May 17, 2026, 1:59 a.m.
NED2 Entity disambiguation (via description) batch_6a09217fdcd08190bc41700ec09851e1 completed May 17, 2026, 2:01 a.m.
Created at: April 16, 2026, 12:48 p.m.