Triple

T16443038
Position Surface form Disambiguated ID Type / Status
Subject Branca of Portugal E399352 entity
Predicate givenName P17 FINISHED
Object Branca
Branca was a medieval Portuguese infanta (princess) of the royal House of Burgundy.
 E1212956 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: Branca | Statement: [Branca of Portugal, givenName, Branca]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07 
Target entity: Branca
Context triple: [Branca of Portugal, givenName, Branca]
  • A. Branca
    Branca is a surname most notably associated with former Major League Baseball pitcher Ralph Branca.
  • B. Bianco
    Bianco is an Italian surname commonly associated with individuals of Italian heritage, including the artist Enrico Bianco.
  • C. Albine
    Albine is a central character in Émile Zola’s novel *La Faute de l’Abbé Mouret*, symbolizing natural innocence and forbidden love in contrast to the priest’s religious devotion.
  • D. Branco
    Branco is a Portuguese surname borne by various notable figures, including architects, artists, and public personalities.
  • E. Redburga
    Redburga is a historically obscure woman believed to have been the wife of King Egbert of Wessex and the mother of King Æthelwulf, placing her in the early 9th-century West Saxon royal family.
  • 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: Branca
Triple: [Branca of Portugal, givenName, Branca]
Generated description
Branca was a medieval Portuguese infanta (princess) of the royal House of Burgundy.
NED2 Entity disambiguation (via description) gpt-5-mini-2025-08-07 
Target entity: Branca
Target entity description: Branca was a medieval Portuguese infanta (princess) of the royal House of Burgundy.
  • A. Branca
    Branca is a surname most notably associated with former Major League Baseball pitcher Ralph Branca.
  • B. Bianco
    Bianco is an Italian surname commonly associated with individuals of Italian heritage, including the artist Enrico Bianco.
  • C. Albine
    Albine is a central character in Émile Zola’s novel *La Faute de l’Abbé Mouret*, symbolizing natural innocence and forbidden love in contrast to the priest’s religious devotion.
  • D. Branco
    Branco is a Portuguese surname borne by various notable figures, including architects, artists, and public personalities.
  • E. Redburga
    Redburga is a historically obscure woman believed to have been the wife of King Egbert of Wessex and the mother of King Æthelwulf, placing her in the early 9th-century West Saxon royal family.
  • 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_69d87f2c6778819080fcfae53be8f12a completed April 10, 2026, 4:40 a.m.
NER Named-entity recognition batch_69e32cd8d2988190acb5722a15623319 completed April 18, 2026, 7:03 a.m.
NED1 Entity disambiguation (via context triple) batch_6a00458f8f3c8190ad5eff2ad2a32dea completed May 10, 2026, 8:45 a.m.
NEDg Description generation batch_6a00461390608190848c3b896042f1fd completed May 10, 2026, 8:47 a.m.
NED2 Entity disambiguation (via description) batch_6a0046a88e048190baa78506808171b8 completed May 10, 2026, 8:49 a.m.
Created at: April 10, 2026, 5:10 a.m.