Triple

T23832205
Position Surface form Disambiguated ID Type / Status
Subject Princess Maria Amélia of Brazil E589543 entity
Predicate fullName P16 FINISHED
Object Maria Amélia de Bragança
Maria Amélia de Bragança was a 19th-century Brazilian princess of the House of Braganza, daughter of Emperor Pedro I of Brazil and Empress Maria Leopoldina.
E1607973 NE FINISHED

How this triple was built (2 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: Maria Amélia de Bragança | Statement: [Princess Maria Amélia of Brazil, fullName, Maria Amélia de Bragança]
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: Maria Amélia de Bragança
Triple: [Princess Maria Amélia of Brazil, fullName, Maria Amélia de Bragança]
Generated description
Maria Amélia de Bragança was a 19th-century Brazilian princess of the House of Braganza, daughter of Emperor Pedro I of Brazil and Empress Maria Leopoldina.

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_69e25d1922d481909cab567c06a802ab completed April 17, 2026, 4:17 p.m.
NER Named-entity recognition batch_69f1c7f6f25c8190bd8957fe3cbefc03 completed April 29, 2026, 8:57 a.m.
NED1 Entity disambiguation (via context triple) batch_6a0f7614173c8190b8ac31044311abe4 completed May 21, 2026, 9:16 p.m.
NEDg Description generation batch_6a0f7763b168819096e38c871623606d completed May 21, 2026, 9:21 p.m.
NED2 Entity disambiguation (via description) batch_6a0f78495eb481908d64e7caa0e065b4 completed May 21, 2026, 9:25 p.m.
Created at: April 17, 2026, 8:06 p.m.