Triple

T32506194
Position Surface form Disambiguated ID Type / Status
Subject Lapa, Rio de Janeiro E830801 entity
Predicate hasPublicSpace P105 FINISHED
Object Praça Cardeal Câmara
Praça Cardeal Câmara is a public square located in the historic Lapa neighborhood of Rio de Janeiro, Brazil, known for its urban setting amid the area’s vibrant cultural and nightlife scene.
E2009592 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: Praça Cardeal Câmara | Statement: [Lapa, Rio de Janeiro, hasPublicSpace, Praça Cardeal Câmara]
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: Praça Cardeal Câmara
Triple: [Lapa, Rio de Janeiro, hasPublicSpace, Praça Cardeal Câmara]
Generated description
Praça Cardeal Câmara is a public square located in the historic Lapa neighborhood of Rio de Janeiro, Brazil, known for its urban setting amid the area’s vibrant cultural and nightlife scene.

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_69f349219cb8819087e120f509629c1b completed April 30, 2026, 12:20 p.m.
NER Named-entity recognition batch_69f6c44b26a88190be979e894c7dfd38 completed May 3, 2026, 3:43 a.m.
NED1 Entity disambiguation (via context triple) batch_6a34705deb6c81909da3a17809c7af55 completed June 18, 2026, 10:25 p.m.
NEDg Description generation batch_6a3470eb59888190b257fd4bb4388959 completed June 18, 2026, 10:27 p.m.
NED2 Entity disambiguation (via description) batch_6a3471ad2e5081908317c104296eb386 completed June 18, 2026, 10:31 p.m.
Created at: May 1, 2026, 1 a.m.