Triple

T7542685
Position Surface form Disambiguated ID Type / Status
Subject Hojai Bushu E178317 entity
Predicate languageContext P36 FINISHED
Object Dimasa language E166026 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: Dimasa language | Statement: [Hojai Bushu, languageContext, Dimasa language]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Dimasa language
Context triple: [Hojai Bushu, languageContext, Dimasa language]
  • A. Dimasa language chosen
    Dimasa is a Tibeto-Burman language spoken primarily by the Dimasa people in the Indian states of Assam and Nagaland.
  • B. Damana language
    The Damana language is an indigenous Chibchan tongue spoken by the Wiwa people of the Sierra Nevada de Santa Marta region in northern Colombia.
  • C. Madura language
    The Madura language is an Austronesian language spoken primarily on Madura Island and in parts of East Java, Indonesia, by the Madurese people.
  • D. Bima language
    Bima language is an Austronesian language spoken primarily on Sumbawa Island in Indonesia, known for its distinct grammar and vocabulary within the region.
  • E. Betawi language
    Betawi language is an Austronesian language variety spoken primarily in Jakarta, Indonesia, known for blending Malay with influences from Javanese, Sundanese, Chinese, Arabic, and Dutch.
  • 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_69c69f2be3888190a6667a27f8f195e9 completed March 27, 2026, 3:15 p.m.
NER Named-entity recognition batch_69c6f8762b048190a0b262f9cb3fe1b0 completed March 27, 2026, 9:36 p.m.
NED1 Entity disambiguation (via context triple) batch_69c84f1d1e148190be015c62ae1ea1e8 completed March 28, 2026, 9:58 p.m.
Created at: March 27, 2026, 3:48 p.m.