Triple

T25680982
Position Surface form Disambiguated ID Type / Status
Subject Baniwa-Curripaco E643937 entity
Predicate region P40 FINISHED
Object Içana River region
The Içana River region is a remote area in the northwest Amazon, spanning parts of Brazil and Colombia, known for its dense rainforest, riverine ecosystems, and long-inhabited Indigenous territories.
E1691135 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: Içana River region | Statement: [Baniwa-Curripaco, region, Içana River region]
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: Içana River region
Triple: [Baniwa-Curripaco, region, Içana River region]
Generated description
The Içana River region is a remote area in the northwest Amazon, spanning parts of Brazil and Colombia, known for its dense rainforest, riverine ecosystems, and long-inhabited Indigenous territories.

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_69e77e8046888190b07ffa58c7e2c37a completed April 21, 2026, 1:41 p.m.
NER Named-entity recognition batch_69f5fb794ba48190bc8f3f503ee7cf01 completed May 2, 2026, 1:26 p.m.
NED1 Entity disambiguation (via context triple) batch_6a10c15f52fc8190a4b36a72c9f7b89f completed May 22, 2026, 8:49 p.m.
NEDg Description generation batch_6a10c22b19a48190b04130bdb7763f0a completed May 22, 2026, 8:52 p.m.
NED2 Entity disambiguation (via description) batch_6a10c2de07648190858ba8901748aa53 completed May 22, 2026, 8:55 p.m.
Created at: April 21, 2026, 7:58 p.m.