Triple

T13293777
Position Surface form Disambiguated ID Type / Status
Subject Selayar Islands Regency E316624 entity
Predicate hasLocalLanguages P35567 FINISHED
Object Selayarese E150101 NE FINISHED

How this triple was built (2 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: Selayarese | Statement: [Selayar Islands Regency, hasLocalLanguages, Selayarese]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Selayarese
Context triple: [Selayar Islands Regency, hasLocalLanguages, Selayarese]
  • A. Selayar language chosen
    The Selayar language is an Austronesian language spoken primarily on Selayar Island in South Sulawesi, Indonesia.
  • B. Kedangese
    Kedangese is an Austronesian language spoken by the Kedang people on Lembata Island in eastern Indonesia.
  • C. Nusa Laut language
    The Nusa Laut language is an Austronesian language spoken on Nusa Laut Island in Indonesia’s Maluku province, belonging to the Central Maluku subgroup.
  • D. Bidayuh language
    The Bidayuh language is an Austronesian language spoken by the Bidayuh people of western Borneo, particularly in the Malaysian state of Sarawak and parts of Indonesian Kalimantan.
  • E. Betawi language
    Betawi language is an Austronesian language variety spoken primarily in Jakarta, Indonesia, known for blending Malay with influences from Javanese, Sundanese, Chinese, Arabic, and Dutch.
  • F. None of above.
  • G. Unsure - the case is ambiguous/there is not enough information to decide.

Provenance (3 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_69d806b349908190a9a61dd9323bf153 completed April 9, 2026, 8:06 p.m.
NER Named-entity recognition batch_69d99078bcf0819083195fb556bcacb2 completed April 11, 2026, 12:06 a.m.
NED1 Entity disambiguation (via context triple) batch_69f716d8ee2081908428339216c43b47 completed May 3, 2026, 9:35 a.m.
Created at: April 9, 2026, 9:28 p.m.