Triple

T25756682
Position Surface form Disambiguated ID Type / Status
Subject Osorio E648619 entity
Predicate hasVariant P455 FINISHED
Object Osório
Osório is a Portuguese surname and given name of Iberian origin, borne by various notable individuals and places in Portuguese- and Spanish-speaking countries.
E1701472 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: Osório | Statement: [Osorio, hasVariant, Osório]
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: Osório
Triple: [Osorio, hasVariant, Osório]
Generated description
Osório is a Portuguese surname and given name of Iberian origin, borne by various notable individuals and places in Portuguese- and Spanish-speaking countries.

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_69e7ab314d788190b3abe19e114080e1 completed April 21, 2026, 4:52 p.m.
NER Named-entity recognition batch_69f5fd83a8c08190a01a2ba975690e38 completed May 2, 2026, 1:34 p.m.
NED1 Entity disambiguation (via context triple) batch_6a10ec9e1290819099c207d2e32e7984 completed May 22, 2026, 11:54 p.m.
NEDg Description generation batch_6a10ee2510588190a304a6c042436217 completed May 23, 2026, midnight
NED2 Entity disambiguation (via description) batch_6a10f04c3c4c8190bd0084b6b1b9e7a7 completed May 23, 2026, 12:09 a.m.
Created at: April 22, 2026, 4:41 a.m.