Triple

T25803254
Position Surface form Disambiguated ID Type / Status
Subject Amazonas State (Venezuela) E649893 entity
Predicate contains P35 FINISHED
Object Sipapo River
The Sipapo River is a tributary waterway in southern Venezuela that flows through remote rainforest regions of Amazonas State and supports local Indigenous communities and biodiversity.
E2054638 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: Sipapo River | Statement: [Amazonas State (Venezuela), contains, Sipapo 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: Sipapo River
Triple: [Amazonas State (Venezuela), contains, Sipapo River]
Generated description
The Sipapo River is a tributary waterway in southern Venezuela that flows through remote rainforest regions of Amazonas State and supports local Indigenous communities and biodiversity.

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_69e7ab34f8c8819099f6c4dabdabf129 completed April 21, 2026, 4:52 p.m.
NER Named-entity recognition batch_69f5ffccd0d0819095d21378b5b9590a completed May 2, 2026, 1:44 p.m.
NED1 Entity disambiguation (via context triple) batch_6a359583c21c819083b2c2d5ac15ad11 completed June 19, 2026, 7:16 p.m.
NEDg Description generation batch_6a35a07b378c81909c246bc347c47ee3 completed June 19, 2026, 8:03 p.m.
NED2 Entity disambiguation (via description) batch_6a35a103368881908241e8cc960d871d completed June 19, 2026, 8:05 p.m.
Created at: April 22, 2026, 6:43 a.m.