Triple

T29629932
Position Surface form Disambiguated ID Type / Status
Subject Nhamundá River region E755544 entity
Predicate hasPart P35 FINISHED
Object Nhamundá River
The Nhamundá River is a tributary of the Amazon River in northern Brazil, known for flowing through remote rainforest areas along the border of the states of Amazonas and Pará.
E1971985 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: Nhamundá River | Statement: [Nhamundá River region, hasPart, Nhamundá 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: Nhamundá River
Triple: [Nhamundá River region, hasPart, Nhamundá River]
Generated description
The Nhamundá River is a tributary of the Amazon River in northern Brazil, known for flowing through remote rainforest areas along the border of the states of Amazonas and Pará.

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_69f0ef88fbe081908f0ad90c1c413f1c completed April 28, 2026, 5:34 p.m.
NER Named-entity recognition batch_69f66e64ac588190a91481917a6e91da completed May 2, 2026, 9:36 p.m.
NED1 Entity disambiguation (via context triple) batch_6a2b79a86f0081908164df3f6099316c completed June 12, 2026, 3:14 a.m.
NEDg Description generation batch_6a2b7a866a408190a377ebe1dfb4b162 completed June 12, 2026, 3:18 a.m.
NED2 Entity disambiguation (via description) batch_6a2b7b5699c48190b83c080aa685a7b4 completed June 12, 2026, 3:21 a.m.
Created at: April 28, 2026, 6:40 p.m.