Triple

T7767655
Position Surface form Disambiguated ID Type / Status
Subject Baniwa language E178989 entity
Predicate alternateName P39 FINISHED
Object Kurripako-Baniwa
Kurripako-Baniwa is an Arawakan language spoken by Indigenous communities in the Upper Rio Negro region of Brazil, Colombia, and Venezuela.
E687245 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: Kurripako-Baniwa | Statement: [Baniwa language, alternateName, Kurripako-Baniwa]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Kurripako-Baniwa
Context triple: [Baniwa language, alternateName, Kurripako-Baniwa]
  • A. Kawayan
    Kawayan is a coastal municipality on Biliran Island in the Eastern Visayas region of the Philippines.
  • B. Yakan
    Yakan is an Austronesian language spoken primarily by the Yakan people of Basilan and nearby areas in the southern Philippines.
  • C. Pilcaniyeu
    Pilcaniyeu is a small town in Argentina’s Patagonia region, located in the Andean area of Río Negro Province and known for its rural character and nearby natural landscapes.
  • D. Ibanag
    Ibanag is an Austronesian language spoken primarily in the Cagayan Valley region of northern Luzon in the Philippines.
  • E. Malabanias
    Malabanias is a barangay (village-level administrative district) within Angeles City in Pampanga, Philippines, known for its mixed residential, commercial, and entertainment areas.
  • 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: Kurripako-Baniwa
Triple: [Baniwa language, alternateName, Kurripako-Baniwa]
Generated description
Kurripako-Baniwa is an Arawakan language spoken by Indigenous communities in the Upper Rio Negro region of Brazil, Colombia, and Venezuela.
NED2 Entity disambiguation (via description) gpt-5-mini-2025-08-07
Target entity: Kurripako-Baniwa
Target entity description: Kurripako-Baniwa is an Arawakan language spoken by Indigenous communities in the Upper Rio Negro region of Brazil, Colombia, and Venezuela.
  • A. Kawayan
    Kawayan is a coastal municipality on Biliran Island in the Eastern Visayas region of the Philippines.
  • B. Yakan
    Yakan is an Austronesian language spoken primarily by the Yakan people of Basilan and nearby areas in the southern Philippines.
  • C. Pilcaniyeu
    Pilcaniyeu is a small town in Argentina’s Patagonia region, located in the Andean area of Río Negro Province and known for its rural character and nearby natural landscapes.
  • D. Ibanag
    Ibanag is an Austronesian language spoken primarily in the Cagayan Valley region of northern Luzon in the Philippines.
  • E. Malabanias
    Malabanias is a barangay (village-level administrative district) within Angeles City in Pampanga, Philippines, known for its mixed residential, commercial, and entertainment areas.
  • 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_69c69f30602c819082ab52cd4af5c592 completed March 27, 2026, 3:16 p.m.
NER Named-entity recognition batch_69c70435b7f88190a5e68e6ae701c58f completed March 27, 2026, 10:27 p.m.
NED1 Entity disambiguation (via context triple) batch_69c8c7e4976c81909ff34dcdcae96999 completed March 29, 2026, 6:34 a.m.
NEDg Description generation batch_69c8c8b75b848190a67de2040d563f86 completed March 29, 2026, 6:37 a.m.
NED2 Entity disambiguation (via description) batch_69c8c941814081909d299df5cd714c71 completed March 29, 2026, 6:40 a.m.
Created at: March 27, 2026, 4:11 p.m.