Triple

T10483591
Position Surface form Disambiguated ID Type / Status
Subject Proto-Koman E247233 entity
Predicate ancestorOf P369 FINISHED
Object Gule language E247232 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: Gule language | Statement: [Proto-Koman, ancestorOf, Gule language]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Gule language
Context triple: [Proto-Koman, ancestorOf, Gule language]
  • A. Gule language chosen
    The Gule language is an endangered Nilo-Saharan language formerly spoken by a small ethnic group in the border region of Sudan and Ethiopia.
  • B. Sanglechi language
    The Sanglechi language is an Eastern Iranian language spoken by a small community in the Sanglech Valley region of Afghanistan and Tajikistan.
  • C. Ngulu language
    The Ngulu language is a Bantu language spoken in parts of East Africa, particularly in Tanzania, and is part of the larger Northeast Coast Bantu subgroup.
  • D. Gura language
    The Gura language is an Ethiopian Semitic language spoken by the Gurage people in central Ethiopia.
  • E. Murle language
    The Murle language is an Eastern Sudanic language spoken primarily by the Murle people of South Sudan.
  • 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_69d381c309b88190af78aa681cf6a4c2 completed April 6, 2026, 9:49 a.m.
NER Named-entity recognition batch_69d509678ac88190984f18a2162e2dcf completed April 7, 2026, 1:40 p.m.
NED1 Entity disambiguation (via context triple) batch_69d8a03c647c81909521fee4a66ec8ac completed April 10, 2026, 7:01 a.m.
Created at: April 6, 2026, 12:22 p.m.