Triple

T37779897
Position Surface form Disambiguated ID Type / Status
Subject Nova Petrópolis E941796 entity
Predicate nickname P55 FINISHED
Object Garden of Serra Gaúcha
Garden of Serra Gaúcha is the affectionate nickname for Nova Petrópolis, a picturesque town in Brazil’s Serra Gaúcha region known for its well-kept gardens, flowers, and scenic alpine landscapes.
E2242224 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: Garden of Serra Gaúcha | Statement: [Nova Petrópolis, nickname, Garden of Serra Gaúcha]
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: Garden of Serra Gaúcha
Triple: [Nova Petrópolis, nickname, Garden of Serra Gaúcha]
Generated description
Garden of Serra Gaúcha is the affectionate nickname for Nova Petrópolis, a picturesque town in Brazil’s Serra Gaúcha region known for its well-kept gardens, flowers, and scenic alpine landscapes.

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_69f76ee4431881908f87e8892a9f39f3 completed May 3, 2026, 3:51 p.m.
NER Named-entity recognition batch_69fbaf48082c8190bf83c4c2c9733c2b completed May 6, 2026, 9:14 p.m.
NED1 Entity disambiguation (via context triple) batch_6a40e08fed3481908567b154f6578561 completed June 28, 2026, 8:51 a.m.
NEDg Description generation batch_6a40e12996ec8190955a5b3c357027c6 completed June 28, 2026, 8:54 a.m.
NED2 Entity disambiguation (via description) batch_6a40e4872fa48190b7a5e2b0497e01cf completed June 28, 2026, 9:08 a.m.
Created at: May 3, 2026, 4:19 p.m.