Triple

T7180012
Position Surface form Disambiguated ID Type / Status
Subject Arosi language E167421 entity
Predicate neighboringLanguage P16383 FINISHED
Object Owa 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: Owa language | Statement: [Arosi language, neighboringLanguage, Owa language]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Owa language
Context triple: [Arosi language, neighboringLanguage, Owa language]
  • A. Okrika language
    The Okrika language is an Ijaw language spoken primarily by the Okrika people in Rivers State, Nigeria, along the Niger Delta.
  • B. Waja language
    The Waja language is a lesser-known Niger-Congo language spoken by the Waja people of northeastern Nigeria.
  • C. Ouma language
    Ouma language is an extinct Papuan language once spoken in the Papuan Tip region of southeastern Papua New Guinea.
  • D. Anywa language
    Anywa language is a Nilotic language spoken primarily by the Anyuak people in South Sudan and western Ethiopia.
  • E. Kwaio language chosen
    The Kwaio language is an Austronesian language spoken by the Kwaio people on Malaita in the Solomon Islands.
  • 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_69c6888a7c548190a3d39b52a393080f completed March 27, 2026, 1:39 p.m.
NER Named-entity recognition batch_69c6e8ba91908190a9055d4e026b655c completed March 27, 2026, 8:29 p.m.
NED1 Entity disambiguation (via context triple) batch_69c7b935eb088190acb0b8a6b75addbb completed March 28, 2026, 11:19 a.m.
Created at: March 27, 2026, 2:49 p.m.