Triple

T6208103
Position Surface form Disambiguated ID Type / Status
Subject Ingushetia E138797 entity
Predicate hasCity P316 FINISHED
Object Karabulak E533897 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: Karabulak | Statement: [Ingushetia, hasCity, Karabulak]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Karabulak
Context triple: [Ingushetia, hasCity, Karabulak]
  • A. Karabulak chosen
    Karabulak is a town in the Republic of Ingushetia, Russia, situated in the North Caucasus region.
  • B. Karabağlar
    Karabağlar is a populous urban district of İzmir, Turkey, known primarily as a residential and commercial area within the city’s metropolitan region.
  • C. Karatay
    Karatay is a central district and municipality within Turkey’s Konya Province, known for its historical sites and role in the urban core of Konya city.
  • D. Korkuteli
    Korkuteli is a town and district in southwestern Turkey known for its agricultural production and cooler highland climate compared to the coastal areas of Antalya Province.
  • E. Atakule
    Atakule is a prominent observation and communications tower in Ankara, Turkey, known for its panoramic city views and revolving restaurant.
  • 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_69c008ada364819096c9e92c74d639b5 completed March 22, 2026, 3:20 p.m.
NER Named-entity recognition batch_69c062870d5881909b8d4e33ff31a907 completed March 22, 2026, 9:43 p.m.
NED1 Entity disambiguation (via context triple) batch_69c16f52829c81909bdd422cbb1eabf4 completed March 23, 2026, 4:50 p.m.
Created at: March 22, 2026, 4:20 p.m.