Triple

T24041825
Position Surface form Disambiguated ID Type / Status
Subject Yagua E595401 entity
Predicate language P15 FINISHED
Object Yagua language
The Yagua language is an indigenous Peba–Yaguan language spoken by the Yagua people of the Amazon rainforest regions of Peru and Colombia.
E1614662 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: Yagua language | Statement: [Yagua, language, Yagua language]
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: Yagua language
Triple: [Yagua, language, Yagua language]
Generated description
The Yagua language is an indigenous Peba–Yaguan language spoken by the Yagua people of the Amazon rainforest regions of Peru and Colombia.

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_69e288c06a908190899cad4531f32c9a completed April 17, 2026, 7:23 p.m.
NER Named-entity recognition batch_69f1d8da38548190b2cc04ce7960ef9c completed April 29, 2026, 10:09 a.m.
NED1 Entity disambiguation (via context triple) batch_6a0f7eb3f9388190b46dfae28ae1ca27 completed May 21, 2026, 9:52 p.m.
NEDg Description generation batch_6a0f7f919f6081909b1286b2f13171f9 completed May 21, 2026, 9:56 p.m.
NED2 Entity disambiguation (via description) batch_6a0f80468e208190813d392e9e478151 completed May 21, 2026, 9:59 p.m.
Created at: April 17, 2026, 9:57 p.m.