Triple

T8938902
Position Surface form Disambiguated ID Type / Status
Subject Makushi language E212846 entity
Predicate alternativeName P39 FINISHED
Object Makuxi
Makuxi is an indigenous people of northern Brazil and neighboring regions, known for their distinct language, culture, and traditional practices in the Amazonian savanna.
 E767333 NE FINISHED

How this triple was built (4 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: Makuxi | Statement: [Makushi language, alternativeName, Makuxi]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07 
Target entity: Makuxi
Context triple: [Makushi language, alternativeName, Makuxi]
  • A. Mazabuka
    Mazabuka is a town in southern Zambia known for its sugar industry and agricultural production.
  • B. Kwaluudhi
    Kwaluudhi is a dialect of the Ovambo language spoken by a specific Ovambo subgroup in northern Namibia.
  • C. Xola
    Xola is a Mexico City Metro station on Line 2 that serves the southern part of the city near the Calzada de Tlalpan corridor.
  • D. Mafadi
    Mafadi is a prominent mountain peak on the border of South Africa and Lesotho, renowned as the highest point in South Africa and a popular destination for serious hikers and mountaineers.
  • E. Mtiuleti
    Mtiuleti is a mountainous historical region in northeastern Georgia known for its rugged landscapes and traditional highland villages.
  • F. None of above. chosen
  • G. Unsure - the case is ambiguous/there is not enough information to decide.
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: Makuxi
Triple: [Makushi language, alternativeName, Makuxi]
Generated description
Makuxi is an indigenous people of northern Brazil and neighboring regions, known for their distinct language, culture, and traditional practices in the Amazonian savanna.
NED2 Entity disambiguation (via description) gpt-5-mini-2025-08-07 
Target entity: Makuxi
Target entity description: Makuxi is an indigenous people of northern Brazil and neighboring regions, known for their distinct language, culture, and traditional practices in the Amazonian savanna.
  • A. Mazabuka
    Mazabuka is a town in southern Zambia known for its sugar industry and agricultural production.
  • B. Kwaluudhi
    Kwaluudhi is a dialect of the Ovambo language spoken by a specific Ovambo subgroup in northern Namibia.
  • C. Xola
    Xola is a Mexico City Metro station on Line 2 that serves the southern part of the city near the Calzada de Tlalpan corridor.
  • D. Mafadi
    Mafadi is a prominent mountain peak on the border of South Africa and Lesotho, renowned as the highest point in South Africa and a popular destination for serious hikers and mountaineers.
  • E. Mtiuleti
    Mtiuleti is a mountainous historical region in northeastern Georgia known for its rugged landscapes and traditional highland villages.
  • F. None of above. chosen

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_69ca839694c88190b324ffeb43d23b08 completed March 30, 2026, 2:07 p.m.
NER Named-entity recognition batch_69cc66b7484481909e0d7610552f5386 completed April 1, 2026, 12:28 a.m.
NED1 Entity disambiguation (via context triple) batch_69cfc1eb308c81909f5be133c75ad568 completed April 3, 2026, 1:34 p.m.
NEDg Description generation batch_69cfc24b4fe481909b7c4f58b787a21e completed April 3, 2026, 1:36 p.m.
NED2 Entity disambiguation (via description) batch_69cfc33fbedc8190a8f04ec6f43891f0 completed April 3, 2026, 1:40 p.m.
Created at: March 30, 2026, 6:58 p.m.