Triple

T19677379
Position Surface form Disambiguated ID Type / Status
Subject Shina language E472489 entity
Predicate hasDialect P4251 FINISHED
Object Guresi Shina NE NERFINISHED

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: Guresi Shina | Statement: [Shina language, hasDialect, Guresi Shina]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Guresi Shina
Context triple: [Shina language, hasDialect, Guresi Shina]
  • A. Haramosh Shina chosen
    Haramosh Shina is a regional dialect of the Shina language spoken in the Haramosh area of northern Pakistan.
  • B. Shina
    Shina is an Indo-Aryan language spoken primarily in the Gilgit-Baltistan region of Pakistan and surrounding Himalayan areas.
  • C. Shizhen
    Shizhen is the given name of Li Shizhen, the renowned Ming dynasty physician and naturalist best known for compiling the monumental Chinese medical text "Compendium of Materia Medica."
  • D. Shiban
    Shiban was a Mongol prince of the Golden Horde, a son of Jochi and grandson of Genghis Khan who founded the Shibanid line.
  • E. Shenir
    Shenir is an alternate name for the Sinyar language, a Nilo-Saharan language spoken by the Sinyar people of western Sudan and eastern Chad.
  • F. None of above.
  • G. Unsure - the case is ambiguous/there is not enough information to decide.

Provenance (2 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_69d8e514f2e08190ba70a4449519d218 completed April 10, 2026, 11:55 a.m.
NER Named-entity recognition batch_69e641bceef881909c5b655af709c8c6 completed April 20, 2026, 3:09 p.m.
Created at: April 10, 2026, 1:45 p.m.