Triple

T34243462
Position Surface form Disambiguated ID Type / Status
Subject Três Rios E878531 entity
Predicate riverConfluenceOf P11843 FINISHED
Object Piabanha River
The Piabanha River is a watercourse in the state of Rio de Janeiro, Brazil, that flows through the mountainous interior before joining other rivers near the city of Três Rios.
E2296335 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: Piabanha River | Statement: [Três Rios, riverConfluenceOf, Piabanha River]
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: Piabanha River
Triple: [Três Rios, riverConfluenceOf, Piabanha River]
Generated description
The Piabanha River is a watercourse in the state of Rio de Janeiro, Brazil, that flows through the mountainous interior before joining other rivers near the city of Três Rios.

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_69f349b3618481909df955b063f305b2 completed April 30, 2026, 12:23 p.m.
NER Named-entity recognition batch_69f71280295c81909a2fcda9df66c359 completed May 3, 2026, 9:16 a.m.
NED1 Entity disambiguation (via context triple) batch_6a82641ca0748190b2de51f616d86380 completed Aug. 17, 2026, 1:30 a.m.
NEDg Description generation batch_6a82646df7c88190ae7780dcfd56a574 completed Aug. 17, 2026, 1:31 a.m.
NED2 Entity disambiguation (via description) batch_6a82649392988190b489df93c21413cb completed Aug. 17, 2026, 1:32 a.m.
Created at: May 1, 2026, 1:56 a.m.