Triple

T6786707
Position Surface form Disambiguated ID Type / Status
Subject Willaumez languages E155824 entity
Predicate hasMember P10 FINISHED
Object Nakanai language E619302 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: Nakanai language | Statement: [Willaumez languages, hasMember, Nakanai language]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Nakanai language
Context triple: [Willaumez languages, hasMember, Nakanai language]
  • A. Nakanai language chosen
    The Nakanai language is an Austronesian language spoken by the Nakanai people of New Britain in Papua New Guinea.
  • B. Kawaiisu language
    Kawaiisu language is an endangered Uto-Aztecan language traditionally spoken by the Kawaiisu people of southern California.
  • C. Mikasuki language
    The Mikasuki language is a Native American Muskogean language traditionally spoken by the Miccosukee and Seminole peoples of Florida.
  • D. Akawaio language
    The Akawaio language is an indigenous Cariban language spoken by the Akawaio people of Guyana, Venezuela, and Brazil.
  • E. Ishkashimi language
    The Ishkashimi language is an Eastern Iranian Pamir language spoken by a small community in the Ishkashim region of Afghanistan and Tajikistan, noted for its endangered status and distinct phonological and grammatical features.
  • 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_69c6881770fc8190972b2906390380f5 completed March 27, 2026, 1:37 p.m.
NER Named-entity recognition batch_69c6d28f043081909a9a9ab635785933 completed March 27, 2026, 6:55 p.m.
NED1 Entity disambiguation (via context triple) batch_69c723cc35cc8190b5affdfd363171ba completed March 28, 2026, 12:41 a.m.
Created at: March 27, 2026, 2:14 p.m.