Triple

T7124534
Position Surface form Disambiguated ID Type / Status
Subject Dimasa language E166026 entity
Predicate closelyRelatedTo P37 FINISHED
Object Bodo language E30589 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: Bodo language | Statement: [Dimasa language, closelyRelatedTo, Bodo language]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Bodo language
Context triple: [Dimasa language, closelyRelatedTo, Bodo language]
  • A. Bodo chosen
    Bodo is a Sino-Tibetan language spoken primarily by the Bodo people in northeastern India, especially in Assam and surrounding regions.
  • B. Karbi language
    The Karbi language is a Tibeto-Burman language spoken primarily by the Karbi people in Northeast India, especially in Assam.
  • C. Banda-Bogbo language
    The Banda-Bogbo language is a Central Sudanic language spoken by the Banda people in parts of the Central African Republic.
  • D. Boro language
    Boro language is a Tibeto-Burman language spoken primarily by the Boro people of Assam in northeastern India.
  • E. Bariai language
    The Bariai language is an Austronesian language spoken by the Bariai people of New Britain in Papua New Guinea.
  • 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_69c6888350588190870cd552b427a1cd completed March 27, 2026, 1:39 p.m.
NER Named-entity recognition batch_69c6e64c0f688190a9b7482d86c2f033 completed March 27, 2026, 8:19 p.m.
NED1 Entity disambiguation (via context triple) batch_69c7a331ff988190886bde89035623c0 completed March 28, 2026, 9:45 a.m.
Created at: March 27, 2026, 2:44 p.m.