Triple

T22933923
Position Surface form Disambiguated ID Type / Status
Subject Tomini languages E569521 entity
Predicate hasMember P10 FINISHED
Object Balaesang language NE NERFINISHED

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: Balaesang language | Statement: [Tomini languages, hasMember, Balaesang language]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Balaesang language
Context triple: [Tomini languages, hasMember, Balaesang language]
  • A. Balantak language
    The Balantak language is an Austronesian language spoken by the Balantak people of eastern Central Sulawesi, Indonesia.
  • B. Baangi language
    The Baangi language is a lesser-known Nupoid (Benue–Congo) language spoken by a small community in Nigeria.
  • C. Kacipo-Bale language
    The Kacipo-Bale language is a Surmic language spoken by the Kacipo and Bale peoples of southwestern Ethiopia and neighboring regions of South Sudan.
  • D. Bafia language
    The Bafia language is a Bantu language spoken primarily by the Bafia people in central Cameroon.
  • E. Batui language chosen
    The Batui language is an Austronesian language spoken in Central Sulawesi, Indonesia, and is part of the Saluan–Banggai subgroup.
  • F. None of above.
  • G. Unsure - the case is ambiguous/there is not enough information to decide.

Provenance (2 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_69e24590862c8190858f180ad302adab completed April 17, 2026, 2:37 p.m.
NER Named-entity recognition batch_69f18134484c8190b7311606c17d058d completed April 29, 2026, 3:55 a.m.
Created at: April 17, 2026, 3:44 p.m.