Triple

T6564815
Position Surface form Disambiguated ID Type / Status
Subject Hiw E153875 entity
Predicate hasAlternativeName P39 FINISHED
Object Hiw language E153875 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: Hiw language | Statement: [Hiw, hasAlternativeName, Hiw language]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Hiw language
Context triple: [Hiw, hasAlternativeName, Hiw language]
  • A. Ho language
    Ho language is an Austroasiatic language of the Munda family spoken primarily by the Ho people in eastern India, particularly in Jharkhand and Odisha.
  • B. Hiw chosen
    Hiw is an Oceanic language spoken on Hiw Island in northern Vanuatu, known for its small speaker population and distinctive phonological features.
  • C. Ha language
    Ha language is a Bantu language spoken primarily by the Ha people in western Tanzania, particularly around the shores of Lake Tanganyika.
  • D. Hewa language
    The Hewa language is a lesser-known Austronesian language spoken on the Indonesian islands of Flores and/or Lembata, belonging to the Flores–Lembata subgroup.
  • E. JW Language
    JW Language is a mobile app developed by Jehovah’s Witnesses to help users learn and practice foreign languages for use in their religious activities.
  • 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_69c6880cb35881909b763eb0125236b9 completed March 27, 2026, 1:37 p.m.
NER Named-entity recognition batch_69c6ae3b9ec8819080f3052556d95810 completed March 27, 2026, 4:20 p.m.
NED1 Entity disambiguation (via context triple) batch_69c6d5622e0481909b0ac0f4e06d19bc completed March 27, 2026, 7:07 p.m.
Created at: March 27, 2026, 1:52 p.m.