Triple

T25473453
Position Surface form Disambiguated ID Type / Status
Subject Matsigenka language E638366 entity
Predicate spokenBy P2181 FINISHED
Object Matsigenka people
The Matsigenka people are an Indigenous group of the Peruvian Amazon known for their forest-based subsistence lifestyle, rich shamanic traditions, and deep ecological knowledge.
E2284660 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: Matsigenka people | Statement: [Matsigenka language, spokenBy, Matsigenka people]
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: Matsigenka people
Triple: [Matsigenka language, spokenBy, Matsigenka people]
Generated description
The Matsigenka people are an Indigenous group of the Peruvian Amazon known for their forest-based subsistence lifestyle, rich shamanic traditions, and deep ecological knowledge.

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_69e75db9b964819096802dcf502e577e completed April 21, 2026, 11:21 a.m.
NER Named-entity recognition batch_69f5f7536d78819096ba361d59d01c4f completed May 2, 2026, 1:08 p.m.
NED1 Entity disambiguation (via context triple) batch_6a43e16bf0c8819082a4fcc96836fb63 completed June 30, 2026, 3:31 p.m.
NEDg Description generation batch_6a43e25cdb708190a6cf2b0364310254 completed June 30, 2026, 3:35 p.m.
NED2 Entity disambiguation (via description) batch_6a43e31ed64881909d4be0364212089e completed June 30, 2026, 3:39 p.m.
Created at: April 21, 2026, 2:24 p.m.