Triple

T34859376
Position Surface form Disambiguated ID Type / Status
Subject da Rocha E1004822 entity
Predicate hasNotableBearer P458 FINISHED
Object António da Rocha Azevedo
António da Rocha Azevedo is a notable individual who bears the Portuguese surname da Rocha, recognized for his prominence in association with that family name.
E2117767 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: António da Rocha Azevedo | Statement: [da Rocha, hasNotableBearer, António da Rocha Azevedo]
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: António da Rocha Azevedo
Triple: [da Rocha, hasNotableBearer, António da Rocha Azevedo]
Generated description
António da Rocha Azevedo is a notable individual who bears the Portuguese surname da Rocha, recognized for his prominence in association with that family name.

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_69f76dbb678081909a247b9b5e1a73ac completed May 3, 2026, 3:46 p.m.
NER Named-entity recognition batch_69f7816425d08190990f80b96b01bc66 completed May 3, 2026, 5:09 p.m.
NED1 Entity disambiguation (via context triple) batch_6a3786d0ea648190a735682a87493eff completed June 21, 2026, 6:38 a.m.
NEDg Description generation batch_6a3787a11bd48190a72d4382e2ad5e32 completed June 21, 2026, 6:41 a.m.
NED2 Entity disambiguation (via description) batch_6a378832f8c88190941a0758cc5cfd86 completed June 21, 2026, 6:44 a.m.
Created at: May 3, 2026, 4 p.m.