Triple

T29907314
Position Surface form Disambiguated ID Type / Status
Subject Humaitá, Rio de Janeiro, Brazil E759573 entity
Predicate hasMainAvenue P461 FINISHED
Object Rua Humaitá
Rua Humaitá is a principal thoroughfare in the Humaitá neighborhood of Rio de Janeiro, Brazil, known for connecting residential areas with key commercial and transit routes near Botafogo and Lagoa.
E1889839 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: Rua Humaitá | Statement: [Humaitá, Rio de Janeiro, Brazil, hasMainAvenue, Rua Humaitá]
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: Rua Humaitá
Triple: [Humaitá, Rio de Janeiro, Brazil, hasMainAvenue, Rua Humaitá]
Generated description
Rua Humaitá is a principal thoroughfare in the Humaitá neighborhood of Rio de Janeiro, Brazil, known for connecting residential areas with key commercial and transit routes near Botafogo and Lagoa.

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_69f224600590819085e148a01c056ef6 completed April 29, 2026, 3:31 p.m.
NER Named-entity recognition batch_69f67756337881908627f7068dc02d9f completed May 2, 2026, 10:14 p.m.
NED1 Entity disambiguation (via context triple) batch_6a26f1ee56f48190a047a86b00096e3d completed June 8, 2026, 4:46 p.m.
NEDg Description generation batch_6a26f35e46b08190b5f66716be384ca9 completed June 8, 2026, 4:52 p.m.
NED2 Entity disambiguation (via description) batch_6a26f46b6b048190ae3168913b1b1ce8 completed June 8, 2026, 4:57 p.m.
Created at: April 29, 2026, 6:09 p.m.