Triple

T6098791
Position Surface form Disambiguated ID Type / Status
Subject Bungku language E135942 entity
Predicate hasAlternativeName P39 FINISHED
Object Boengkoe
Boengkoe is an alternative name for the Bungku language, an Austronesian language spoken in Southeast Sulawesi, Indonesia.
E569503 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: Boengkoe | Statement: [Bungku language, hasAlternativeName, Boengkoe]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Boengkoe
Context triple: [Bungku language, hasAlternativeName, Boengkoe]
  • A. Kusno
    Kusno was the birth name of Sukarno, the first President of Indonesia and a leading figure in the country’s independence movement.
  • B. Bantia
    Bantia was an ancient Oscan-speaking city in southern Italy, notable for yielding important inscriptions that illuminate the Oscan language and Italic legal traditions.
  • C. Gadjang
    Gadjang is an Aboriginal Australian language variety associated with the Worimi people of New South Wales.
  • D. Pakpak Keppas
    Pakpak Keppas is a regional dialect of the Pakpak Dairi language spoken by the Pakpak ethnic community in parts of North Sumatra, Indonesia.
  • E. Tumpang
    Tumpang is a subdistrict in Malang Regency, East Java, Indonesia, known for its proximity to historical temples and as a gateway to the Bromo-Tengger-Semeru area.
  • 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: Boengkoe
Triple: [Bungku language, hasAlternativeName, Boengkoe]
Generated description
Boengkoe is an alternative name for the Bungku language, an Austronesian language spoken in Southeast Sulawesi, Indonesia.
NED2 Entity disambiguation (via description) gpt-5-mini-2025-08-07
Target entity: Boengkoe
Target entity description: Boengkoe is an alternative name for the Bungku language, an Austronesian language spoken in Southeast Sulawesi, Indonesia.
  • A. Kusno
    Kusno was the birth name of Sukarno, the first President of Indonesia and a leading figure in the country’s independence movement.
  • B. Bantia
    Bantia was an ancient Oscan-speaking city in southern Italy, notable for yielding important inscriptions that illuminate the Oscan language and Italic legal traditions.
  • C. Gadjang
    Gadjang is an Aboriginal Australian language variety associated with the Worimi people of New South Wales.
  • D. Pakpak Keppas
    Pakpak Keppas is a regional dialect of the Pakpak Dairi language spoken by the Pakpak ethnic community in parts of North Sumatra, Indonesia.
  • E. Tumpang
    Tumpang is a subdistrict in Malang Regency, East Java, Indonesia, known for its proximity to historical temples and as a gateway to the Bromo-Tengger-Semeru area.
  • 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_69c0087cd3c48190b459848c72d84eb1 completed March 22, 2026, 3:19 p.m.
NER Named-entity recognition batch_69c05a9a02888190ac201acd14c3fc31 completed March 22, 2026, 9:09 p.m.
NED1 Entity disambiguation (via context triple) batch_69c125475548819086b733a80056eba5 completed March 23, 2026, 11:34 a.m.
NEDg Description generation batch_69c128753cd8819096edb3c817bfae10 completed March 23, 2026, 11:48 a.m.
NED2 Entity disambiguation (via description) batch_69c129134ce08190ada54a7b3eda27f4 completed March 23, 2026, 11:50 a.m.
Created at: March 22, 2026, 4:13 p.m.