Triple

T10321695
Position Surface form Disambiguated ID Type / Status
Subject Tur Abdin E242151 entity
Predicate traditionalLanguage P6149 FINISHED
Object Turoyo E105663 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: Turoyo | Statement: [Tur Abdin, traditionalLanguage, Turoyo]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Turoyo
Context triple: [Tur Abdin, traditionalLanguage, Turoyo]
  • A. Turoyo chosen
    Turoyo is a modern Neo-Aramaic language traditionally spoken by Syriac Orthodox Christian communities from the Tur Abdin region of southeastern Turkey and neighboring areas.
  • B. Talysh
    The Talysh are an Iranian ethnic group primarily inhabiting the southwestern coast of the Caspian Sea in northern Iran and southeastern Azerbaijan, with their own distinct Talysh language and cultural traditions.
  • C. Turiysk
    Turiysk is a small town in western Ukraine known for its historical roots and location within the Volyn region.
  • D. Seraiki
    Seraiki is an Indo-Aryan language spoken primarily in central and southern Pakistan, especially in the southern Punjab region.
  • E. Tosk
    Tosk is the southern variety of Albanian that forms the basis of the standard Albanian language.
  • 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_69d381ac38808190a8ca7457c85b625b completed April 6, 2026, 9:49 a.m.
NER Named-entity recognition batch_69d4d6cce38c8190bfa0f2fb53ed0065 completed April 7, 2026, 10:05 a.m.
NED1 Entity disambiguation (via context triple) batch_69d71d9b2ad881909f3076f8f9d1b1d3 completed April 9, 2026, 3:31 a.m.
Created at: April 6, 2026, 11:50 a.m.