Triple

T13662019
Position Surface form Disambiguated ID Type / Status
Subject Bughotu E327020 entity
Predicate hasAlternativeName P39 FINISHED
Object Bughotu language E141927 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: Bughotu language | Statement: [Bughotu, hasAlternativeName, Bughotu language]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Bughotu language
Context triple: [Bughotu, hasAlternativeName, Bughotu language]
  • A. Buga language
    The Buga language is a lesser-known member of the Khoe family of southern African languages, spoken by a small community and considered endangered.
  • B. Bugotu language chosen
    The Bugotu language is an Oceanic language spoken by the Bugotu people of Santa Isabel Island in the Solomon Islands.
  • C. Bokoto language
    The Bokoto language is a Gbaya language spoken by the Bokoto people of Central Africa, primarily in the Central African Republic and surrounding regions.
  • D. Budong-Budong language
    The Budong-Budong language is an Austronesian language spoken by a small community in West Sulawesi, Indonesia.
  • E. Daakaka language
    The Daakaka language is an Oceanic language spoken by communities on Ambrym Island in Vanuatu.
  • 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_69d8076d8270819092afc2f0e9c359a8 completed April 9, 2026, 8:09 p.m.
NER Named-entity recognition batch_69dbc620df208190afaccf3ddd10aa60 completed April 12, 2026, 4:19 p.m.
NED1 Entity disambiguation (via context triple) batch_69f78b08d27c8190badc612c26423c0e completed May 3, 2026, 5:51 p.m.
Created at: April 9, 2026, 9:52 p.m.