Triple

T24769609
Position Surface form Disambiguated ID Type / Status
Subject Mehinako E619683 entity
Predicate ritualPractice P4193 FINISHED
Object Kuarup ceremony
The Kuarup ceremony is a traditional funerary ritual of several Indigenous peoples of Brazil’s Upper Xingu, honoring the dead through elaborate communal gatherings, dances, and offerings.
E1650566 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: Kuarup ceremony | Statement: [Mehinako, ritualPractice, Kuarup ceremony]
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: Kuarup ceremony
Triple: [Mehinako, ritualPractice, Kuarup ceremony]
Generated description
The Kuarup ceremony is a traditional funerary ritual of several Indigenous peoples of Brazil’s Upper Xingu, honoring the dead through elaborate communal gatherings, dances, and offerings.

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_69e2fabd04488190a2d13c97be745a2d completed April 18, 2026, 3:30 a.m.
NER Named-entity recognition batch_69f410a8dc8081909e2f4b65485a6786 completed May 1, 2026, 2:32 a.m.
NED1 Entity disambiguation (via context triple) batch_6a101c182eb08190a6e7039f51173f25 completed May 22, 2026, 9:04 a.m.
NEDg Description generation batch_6a10248751648190aabfa72ad8ab0b3f completed May 22, 2026, 9:40 a.m.
NED2 Entity disambiguation (via description) batch_6a10258f82b4819095231c1c9398b2c8 completed May 22, 2026, 9:44 a.m.
Created at: April 18, 2026, 4:29 a.m.