Triple

T29076650
Position Surface form Disambiguated ID Type / Status
Subject Sapucaí River E735958 entity
Predicate tributaryOf P415 FINISHED
Object Rio Grande (Brazil)
Rio Grande (Brazil) is a major river in southeastern Brazil that flows through the states of Minas Gerais and São Paulo and forms part of the upper Paraná River basin.
E1957166 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: Rio Grande (Brazil) | Statement: [Sapucaí River, tributaryOf, Rio Grande (Brazil)]
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: Rio Grande (Brazil)
Triple: [Sapucaí River, tributaryOf, Rio Grande (Brazil)]
Generated description
Rio Grande (Brazil) is a major river in southeastern Brazil that flows through the states of Minas Gerais and São Paulo and forms part of the upper Paraná River basin.

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_69f077e9b0a48190bb79548279cb7f64 completed April 28, 2026, 9:03 a.m.
NER Named-entity recognition batch_69f660fdf5f08190b36e506672b64683 completed May 2, 2026, 8:39 p.m.
NED1 Entity disambiguation (via context triple) batch_6a2a1e03808481909364a13bb477f84d completed June 11, 2026, 2:31 a.m.
NEDg Description generation batch_6a2a4bf65d2081909c19bc77b80c2816 completed June 11, 2026, 5:47 a.m.
NED2 Entity disambiguation (via description) batch_6a2a4c8bdd048190861edb67e09827ba completed June 11, 2026, 5:50 a.m.
Created at: April 28, 2026, 10:23 a.m.