Triple

T6381837
Position Surface form Disambiguated ID Type / Status
Subject Pamona language E143600 entity
Predicate hasDialect P4251 FINISHED
Object Tentena dialect
The Tentena dialect is a regional variety of the Pamona language spoken primarily around the town of Tentena in Central Sulawesi, Indonesia.
E588802 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: Tentena dialect | Statement: [Pamona language, hasDialect, Tentena dialect]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Tentena dialect
Context triple: [Pamona language, hasDialect, Tentena dialect]
  • A. Turu dialect
    Turu dialect is a regional variety of the Berom language spoken by Berom communities in parts of central Nigeria.
  • B. Malgavet dialect
    The Malgavet dialect is a regional variety of the Lihir language spoken on the Lihir Islands of Papua New Guinea.
  • C. Vegliot dialect
    The Vegliot dialect is an extinct variety of the Dalmatian Romance language once spoken on the island of Krk (Veglia) in the Adriatic Sea.
  • D. Krakolye dialect
    The Krakolye dialect is a regional variety of the Votic language traditionally spoken in and around the village of Krakolye in Ingria.
  • E. Lutsi dialect
    The Lutsi dialect is an extinct variety of South Estonian once spoken by a small Estonian-speaking community in eastern Latvia.
  • 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: Tentena dialect
Triple: [Pamona language, hasDialect, Tentena dialect]
Generated description
The Tentena dialect is a regional variety of the Pamona language spoken primarily around the town of Tentena in Central Sulawesi, Indonesia.
NED2 Entity disambiguation (via description) gpt-5-mini-2025-08-07
Target entity: Tentena dialect
Target entity description: The Tentena dialect is a regional variety of the Pamona language spoken primarily around the town of Tentena in Central Sulawesi, Indonesia.
  • A. Turu dialect
    Turu dialect is a regional variety of the Berom language spoken by Berom communities in parts of central Nigeria.
  • B. Malgavet dialect
    The Malgavet dialect is a regional variety of the Lihir language spoken on the Lihir Islands of Papua New Guinea.
  • C. Vegliot dialect
    The Vegliot dialect is an extinct variety of the Dalmatian Romance language once spoken on the island of Krk (Veglia) in the Adriatic Sea.
  • D. Krakolye dialect
    The Krakolye dialect is a regional variety of the Votic language traditionally spoken in and around the village of Krakolye in Ingria.
  • E. Lutsi dialect
    The Lutsi dialect is an extinct variety of South Estonian once spoken by a small Estonian-speaking community in eastern Latvia.
  • 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_69c008dac1ec81909cef8157ccd69962 completed March 22, 2026, 3:20 p.m.
NER Named-entity recognition batch_69c0685385948190938b67bff671072b completed March 22, 2026, 10:08 p.m.
NED1 Entity disambiguation (via context triple) batch_69c62db397f48190bc4533ce26b27a55 completed March 27, 2026, 7:11 a.m.
NEDg Description generation batch_69c62f1923408190996ba6dbb5bab651 completed March 27, 2026, 7:17 a.m.
NED2 Entity disambiguation (via description) batch_69c62f9797188190afb5313176e34864 completed March 27, 2026, 7:19 a.m.
Created at: March 22, 2026, 4:34 p.m.