Triple

T7051168
Position Surface form Disambiguated ID Type / Status
Subject Pasan language E163767 entity
Predicate neighboringLanguage P16383 FINISHED
Object Tontemboan language E168657 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: Tontemboan language | Statement: [Pasan language, neighboringLanguage, Tontemboan language]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Tontemboan language
Context triple: [Pasan language, neighboringLanguage, Tontemboan language]
  • A. Tontemboan language chosen
    The Tontemboan language is an Austronesian language spoken by the Tontemboan people of North Sulawesi, Indonesia, and is one of the traditional Minahasan languages of the region.
  • B. Banda-Ndélé language
    The Banda-Ndélé language is a Central Sudanic language spoken by the Banda people, primarily in the Central African Republic.
  • C. Bafut language
    The Bafut language is a Grassfields Bantu language spoken primarily by the Bafut people in the Northwest Region of Cameroon.
  • D. Banda-Mbrém language
    The Banda-Mbrém language is a Central Sudanic language spoken by the Banda people in parts of Central Africa, particularly in the Central African Republic.
  • E. Sanglechi language
    The Sanglechi language is an Eastern Iranian language spoken by a small community in the Sanglech Valley region of Afghanistan and Tajikistan.
  • 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_69c6885f598c8190b6b6495c59d8d962 completed March 27, 2026, 1:38 p.m.
NER Named-entity recognition batch_69c6e2500570819087200013d859cfe6 completed March 27, 2026, 8:02 p.m.
NED1 Entity disambiguation (via context triple) batch_69c7944535bc819086b7648d95b81e37 completed March 28, 2026, 8:41 a.m.
Created at: March 27, 2026, 2:37 p.m.