Triple

T7627506
Position Surface form Disambiguated ID Type / Status
Subject Malaita languages E172672 entity
Predicate hasMember P10 FINISHED
Object Kwaio language E179008 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: Kwaio language | Statement: [Malaita languages, hasMember, Kwaio language]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Kwaio language
Context triple: [Malaita languages, hasMember, Kwaio language]
  • A. Kwaio language chosen
    The Kwaio language is an Austronesian language spoken by the Kwaio people on Malaita in the Solomon Islands.
  • B. Kumbewaha language
    The Kumbewaha language is an Austronesian language spoken in Sulawesi, Indonesia, belonging to the Wotu–Wolio subgroup.
  • C. Kuanua language
    The Kuanua language is an Austronesian language spoken primarily by the Tolai people of East New Britain in Papua New Guinea.
  • D. Akawaio language
    The Akawaio language is an indigenous Cariban language spoken by the Akawaio people of Guyana, Venezuela, and Brazil.
  • E. Zaiwa language
    The Zaiwa language is a Tibeto-Burman language spoken primarily by the Zaiwa people in parts of Yunnan, China and northern Myanmar.
  • 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_69c699517e348190bd3348b6889200f2 completed March 27, 2026, 2:50 p.m.
NER Named-entity recognition batch_69c6fa8150ac8190908aec411b0f4e50 completed March 27, 2026, 9:45 p.m.
NED1 Entity disambiguation (via context triple) batch_69c870aa0b048190afe78ce262834f22 completed March 29, 2026, 12:22 a.m.
Created at: March 27, 2026, 3:56 p.m.