Triple

T25473413
Position Surface form Disambiguated ID Type / Status
Subject Northern Maipurean E638365 entity
Predicate hasMember P10 FINISHED
Object Mandahuaca language
The Mandahuaca language is an indigenous Northern Maipurean (Arawakan) language spoken by the Mandahuaca people of the Amazon region in Venezuela and Brazil.
E1689730 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: Mandahuaca language | Statement: [Northern Maipurean, hasMember, Mandahuaca 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: Mandahuaca language
Triple: [Northern Maipurean, hasMember, Mandahuaca language]
Generated description
The Mandahuaca language is an indigenous Northern Maipurean (Arawakan) language spoken by the Mandahuaca people of the Amazon region in Venezuela and Brazil.

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_6a10c1244a448190976e7ca384d23fc1 completed May 22, 2026, 8:48 p.m.
NEDg Description generation batch_6a10c20f4f748190bc19a702f0788086 completed May 22, 2026, 8:52 p.m.
NED2 Entity disambiguation (via description) batch_6a10c2b5aab88190ab29798dc74baacf completed May 22, 2026, 8:55 p.m.
Created at: April 21, 2026, 2:24 p.m.