Triple

T30068030
Position Surface form Disambiguated ID Type / Status
Subject Parque da Cidade de Niterói E764090 entity
Predicate locatedNear P294 FINISHED
Object São Francisco neighborhood
The São Francisco neighborhood is a coastal district in Niterói, Brazil, known for its residential character, seaside views, and proximity to major urban parks and cultural attractions.
E1899286 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: São Francisco neighborhood | Statement: [Parque da Cidade de Niterói, locatedNear, São Francisco neighborhood]
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: São Francisco neighborhood
Triple: [Parque da Cidade de Niterói, locatedNear, São Francisco neighborhood]
Generated description
The São Francisco neighborhood is a coastal district in Niterói, Brazil, known for its residential character, seaside views, and proximity to major urban parks and cultural attractions.

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_69f2247221388190a13a22c47094a0ef completed April 29, 2026, 3:32 p.m.
NER Named-entity recognition batch_69f67ca8df14819083dc87428b146e8c completed May 2, 2026, 10:37 p.m.
NED1 Entity disambiguation (via context triple) batch_6a2743163f588190a6aa957ec8671a0c completed June 8, 2026, 10:32 p.m.
NEDg Description generation batch_6a2743cf9c208190965b51fdc3713824 completed June 8, 2026, 10:35 p.m.
NED2 Entity disambiguation (via description) batch_6a27448fcf748190a4e15ef2f89f56f5 completed June 8, 2026, 10:39 p.m.
Created at: April 29, 2026, 7 p.m.