Triple

T3703662
Position Surface form Disambiguated ID Type / Status
Subject Kendari E80839 entity
Predicate localLanguages P10892 FINISHED
Object Tolaki language E135941 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: Tolaki language | Statement: [Kendari, localLanguages, Tolaki language]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Tolaki language
Context triple: [Kendari, localLanguages, Tolaki language]
  • A. Tolaki language chosen
    The Tolaki language is an Austronesian language spoken by the Tolaki people of southeastern Sulawesi, Indonesia.
  • B. Tolai language
    The Tolai language is an Austronesian language spoken primarily by the Tolai people of East New Britain in Papua New Guinea.
  • C. Lakalai language
    The Lakalai language is an Austronesian language spoken by the Lakalai people of New Britain in Papua New Guinea.
  • D. Tokodede language
    Tokodede is an Austronesian language spoken primarily in the Liquiçá region of northwestern East Timor.
  • E. Tadaksahak language
    The Tadaksahak language is a Northern Songhay language spoken primarily by the pastoralist Tadaksahak (Idaksahak) people of Mali, influenced by both Berber and Tuareg languages.
  • 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_69ad8b1793888190a5f70e4b21dc05a1 completed March 8, 2026, 2:43 p.m.
NER Named-entity recognition batch_69adc54aaac88190b775dba2513b6d4a completed March 8, 2026, 6:51 p.m.
NED1 Entity disambiguation (via context triple) batch_69b4cdf822348190bf95f7d119c6265a completed March 14, 2026, 2:54 a.m.
Created at: March 8, 2026, 3:33 p.m.