Triple

T5790273
Position Surface form Disambiguated ID Type / Status
Subject Buginese language E128374 entity
Predicate hasNativeName P1435 FINISHED
Object Basa Ugi
Basa Ugi is the native name for the Buginese language spoken by the Bugis people of South Sulawesi, Indonesia.
 E547394 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: Basa Ugi | Statement: [Buginese language, hasNativeName, Basa Ugi]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07 
Target entity: Basa Ugi
Context triple: [Buginese language, hasNativeName, Basa Ugi]
  • A. Winaray
    Winaray is an Austronesian language spoken primarily in the Eastern Visayas region of the Philippines, particularly in Samar, northern Leyte, and nearby areas.
  • B. Kanak Sprak
    Kanak Sprak is a groundbreaking collection of interviews and monologues that captures the street language, identity, and experiences of Turkish-German youth in 1990s Germany.
  • C. Kichwa
    Kichwa is a Quechuan indigenous language variety widely spoken by Andean communities in Ecuador and neighboring regions.
  • D. Kituba
    Kituba is a widely spoken Bantu-based creole language of Central Africa, serving as a major lingua franca in the Republic of the Congo and surrounding regions.
  • E. Dili
    Dili is the coastal capital and largest city of Timor-Leste, serving as its political, economic, and cultural center.
  • 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: Basa Ugi
Triple: [Buginese language, hasNativeName, Basa Ugi]
Generated description
Basa Ugi is the native name for the Buginese language spoken by the Bugis people of South Sulawesi, Indonesia.
NED2 Entity disambiguation (via description) gpt-5-mini-2025-08-07 
Target entity: Basa Ugi
Target entity description: Basa Ugi is the native name for the Buginese language spoken by the Bugis people of South Sulawesi, Indonesia.
  • A. Winaray
    Winaray is an Austronesian language spoken primarily in the Eastern Visayas region of the Philippines, particularly in Samar, northern Leyte, and nearby areas.
  • B. Kanak Sprak
    Kanak Sprak is a groundbreaking collection of interviews and monologues that captures the street language, identity, and experiences of Turkish-German youth in 1990s Germany.
  • C. Kichwa
    Kichwa is a Quechuan indigenous language variety widely spoken by Andean communities in Ecuador and neighboring regions.
  • D. Kituba
    Kituba is a widely spoken Bantu-based creole language of Central Africa, serving as a major lingua franca in the Republic of the Congo and surrounding regions.
  • E. Dili
    Dili is the coastal capital and largest city of Timor-Leste, serving as its political, economic, and cultural center.
  • 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_69c0084450048190bc647b649a05136b completed March 22, 2026, 3:18 p.m.
NER Named-entity recognition batch_69c02a5585788190821b8da40259e0e7 completed March 22, 2026, 5:43 p.m.
NED1 Entity disambiguation (via context triple) batch_69c09820f5c08190811e848eb44ce5b9 completed March 23, 2026, 1:32 a.m.
NEDg Description generation batch_69c0990bf38081908c09c5dfe660c35b completed March 23, 2026, 1:36 a.m.
NED2 Entity disambiguation (via description) batch_69c099b4bc4481909e7cf6886e5ccbea completed March 23, 2026, 1:39 a.m.
Created at: March 22, 2026, 3:51 p.m.