Triple

T7124693
Position Surface form Disambiguated ID Type / Status
Subject Boro language E166029 entity
Predicate closelyRelatedTo P37 FINISHED
Object Garo language E644025 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: Garo language | Statement: [Boro language, closelyRelatedTo, Garo language]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Garo language
Context triple: [Boro language, closelyRelatedTo, Garo language]
  • A. Garo language chosen
    The Garo language is a Tibeto-Burman language spoken primarily by the Garo people of northeastern India and neighboring Bangladesh.
  • B. Gurma language
    Gurma language is a Gur language spoken primarily in parts of Burkina Faso, Togo, Benin, and neighboring West African countries.
  • C. Sanglechi language
    The Sanglechi language is an Eastern Iranian language spoken by a small community in the Sanglech Valley region of Afghanistan and Tajikistan.
  • D. Murle language
    The Murle language is an Eastern Sudanic language spoken primarily by the Murle people of South Sudan.
  • E. Saho language
    The Saho language is an Afroasiatic Cushitic language spoken primarily by the Saho people in Eritrea and northern Ethiopia.
  • 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_69c7ad899dc081908808dc60015fd19e completed March 28, 2026, 10:29 a.m.
Created at: March 27, 2026, 2:44 p.m.