Triple

T5283491
Position Surface form Disambiguated ID Type / Status
Subject Sasak E119554 entity
Predicate hasDialects P4251 FINISHED
Object Ngeno-Ngene
Ngeno-Ngene is a major dialect of the Sasak language spoken on the island of Lombok in Indonesia.
E508398 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: Ngeno-Ngene | Statement: [Sasak, hasDialects, Ngeno-Ngene]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Ngeno-Ngene
Context triple: [Sasak, hasDialects, Ngeno-Ngene]
  • A. Ngenechen
    Ngenechen is the supreme creator deity in Mapuche spirituality, embodying the protective and life-giving force that governs the natural and human world.
  • B. Igunga
    Igunga is a town and district in central Tanzania known for its agricultural activities, particularly cotton and livestock farming, within the Tabora Region.
  • C. Oshikwanyama
    Oshikwanyama is a Bantu language variety spoken primarily in northern Namibia and southern Angola, recognized as one of the major dialects of Oshiwambo.
  • D. Mbanderu
    Mbanderu is a subgroup of the Herero people with its own distinct dialect and cultural traditions, primarily found in Namibia and Botswana.
  • E. Nodwengu
    Nodwengu was a principal royal residence and political center of the Zulu Kingdom during the 19th century.
  • 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: Ngeno-Ngene
Triple: [Sasak, hasDialects, Ngeno-Ngene]
Generated description
Ngeno-Ngene is a major dialect of the Sasak language spoken on the island of Lombok in Indonesia.
NED2 Entity disambiguation (via description) gpt-5-mini-2025-08-07
Target entity: Ngeno-Ngene
Target entity description: Ngeno-Ngene is a major dialect of the Sasak language spoken on the island of Lombok in Indonesia.
  • A. Ngenechen
    Ngenechen is the supreme creator deity in Mapuche spirituality, embodying the protective and life-giving force that governs the natural and human world.
  • B. Igunga
    Igunga is a town and district in central Tanzania known for its agricultural activities, particularly cotton and livestock farming, within the Tabora Region.
  • C. Oshikwanyama
    Oshikwanyama is a Bantu language variety spoken primarily in northern Namibia and southern Angola, recognized as one of the major dialects of Oshiwambo.
  • D. Mbanderu
    Mbanderu is a subgroup of the Herero people with its own distinct dialect and cultural traditions, primarily found in Namibia and Botswana.
  • E. Nodwengu
    Nodwengu was a principal royal residence and political center of the Zulu Kingdom during the 19th century.
  • 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_69bd446d05a8819092ad333a3f9c8d5c completed March 20, 2026, 12:58 p.m.
NER Named-entity recognition batch_69bd84c8d2bc8190840699e5a526b756 completed March 20, 2026, 5:32 p.m.
NED1 Entity disambiguation (via context triple) batch_69bf06e6200881908da623e8548ec051 completed March 21, 2026, 9 p.m.
NEDg Description generation batch_69bf09d1b9088190a7bf560c8d22d225 completed March 21, 2026, 9:12 p.m.
NED2 Entity disambiguation (via description) batch_69bf0a77e3b88190904c5ed6ee48ee71 completed March 21, 2026, 9:15 p.m.
Created at: March 20, 2026, 1:52 p.m.