Triple

T4863797
Position Surface form Disambiguated ID Type / Status
Subject Januária of Brazil E108720 entity
Predicate givenName P17 FINISHED
Object Januária
Januária was a Brazilian princess of the Empire of Brazil, daughter of Emperor Pedro I and heir presumptive before the birth of her younger brother Pedro II.
 E475542 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: Januária | Statement: [Januária of Brazil, givenName, Januária]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07 
Target entity: Januária
Context triple: [Januária of Brazil, givenName, Januária]
  • A. Maio
    Maio is one of the main islands of Cape Verde, known for its quiet beaches, salt flats, and relatively flat, arid landscape.
  • B. Nivôse
    Nivôse is the fourth month of the French Republican Calendar, corresponding roughly to late December and early January and associated with snow and winter.
  • C. Fabvier
    Fabvier was a prominent French Philhellene and military officer who played a key role in supporting the Greek War of Independence in the early 19th century.
  • D. Kislev
    Kislev is a late autumn/early winter month in the Hebrew calendar traditionally associated with the festival of Hanukkah.
  • E. The Tenth Month
    The Tenth Month is a 1970 novel by Laura Z. Hobson that explores the emotional and social challenges faced by a middle-aged, unmarried woman who becomes pregnant.
  • 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: Januária
Triple: [Januária of Brazil, givenName, Januária]
Generated description
Januária was a Brazilian princess of the Empire of Brazil, daughter of Emperor Pedro I and heir presumptive before the birth of her younger brother Pedro II.
NED2 Entity disambiguation (via description) gpt-5-mini-2025-08-07 
Target entity: Januária
Target entity description: Januária was a Brazilian princess of the Empire of Brazil, daughter of Emperor Pedro I and heir presumptive before the birth of her younger brother Pedro II.
  • A. Maio
    Maio is one of the main islands of Cape Verde, known for its quiet beaches, salt flats, and relatively flat, arid landscape.
  • B. Nivôse
    Nivôse is the fourth month of the French Republican Calendar, corresponding roughly to late December and early January and associated with snow and winter.
  • C. Fabvier
    Fabvier was a prominent French Philhellene and military officer who played a key role in supporting the Greek War of Independence in the early 19th century.
  • D. Kislev
    Kislev is a late autumn/early winter month in the Hebrew calendar traditionally associated with the festival of Hanukkah.
  • E. The Tenth Month
    The Tenth Month is a 1970 novel by Laura Z. Hobson that explores the emotional and social challenges faced by a middle-aged, unmarried woman who becomes pregnant.
  • 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_69bd440b965081908b0557721cae6338 completed March 20, 2026, 12:56 p.m.
NER Named-entity recognition batch_69bd6d7718e48190af4c0d1abfa87795 completed March 20, 2026, 3:53 p.m.
NED1 Entity disambiguation (via context triple) batch_69be5cfdb3248190a16a5f3fb97d4950 completed March 21, 2026, 8:55 a.m.
NEDg Description generation batch_69be607df6648190be22b5bc0d6531b4 completed March 21, 2026, 9:10 a.m.
NED2 Entity disambiguation (via description) batch_69be611da7c08190b644cfbcb30741fc completed March 21, 2026, 9:13 a.m.
Created at: March 20, 2026, 1:26 p.m.