Triple

T4759345
Position Surface form Disambiguated ID Type / Status
Subject Turoyo E105663 entity
Predicate traditionalRegion P1968 FINISHED
Object Tur Abdin E242151 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: Tur Abdin | Statement: [Turoyo, traditionalRegion, Tur Abdin]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Tur Abdin
Context triple: [Turoyo, traditionalRegion, Tur Abdin]
  • A. Tur Abdin chosen
    Tur Abdin is a hilly region in southeastern Turkey historically inhabited by Syriac-Assyrian Christians, known for its ancient monasteries and enduring Aramaic-speaking communities.
  • B. Bung Hatta
    Bung Hatta is the affectionate nickname of Mohammad Hatta, the Indonesian independence leader and first vice president of Indonesia.
  • C. Fetha Nagast
    Fetha Nagast is a historic Ethiopian legal code written in Ge'ez that served for centuries as a foundational source of both civil and ecclesiastical law in Ethiopia.
  • D. Alaeddin Hill
    Alaeddin Hill is a prominent historic mound and park in central Konya, Turkey, known for its ancient citadel ruins and panoramic views of the city.
  • E. Quddus
    Quddus is a television personality best known as one of the prominent hosts of MTV’s music video countdown show "Total Request Live" in the early 2000s.
  • 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_69bd43f14cac819081c7c69803648211 completed March 20, 2026, 12:56 p.m.
NER Named-entity recognition batch_69bd650c11f4819098cd1f490f711dc8 completed March 20, 2026, 3:17 p.m.
NED1 Entity disambiguation (via context triple) batch_69be3a77eb848190877eb5e15c7e6b0c completed March 21, 2026, 6:28 a.m.
Created at: March 20, 2026, 1:20 p.m.