Triple

T4526875
Position Surface form Disambiguated ID Type / Status
Subject Konya Province E106200 entity
Predicate hasDistrict P459 FINISHED
Object Akşehir E306192 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: Akşehir | Statement: [Konya Province, hasDistrict, Akşehir]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Akşehir
Context triple: [Konya Province, hasDistrict, Akşehir]
  • A. Akşehir chosen
    Akşehir is a town in central Turkey historically notable as a key strategic hub during the Turkish War of Independence.
  • B. Aksaray
    Aksaray is a historic city in central Turkey known for its location on the ancient Silk Road and its proximity to the Cappadocia region.
  • C. Keçiören
    Keçiören is a densely populated metropolitan district and municipality of Ankara, known as one of the capital city’s major residential and commercial areas.
  • D. Nallıhan
    Nallıhan is a district and town in Turkey known for its natural landscapes, including colorful rock formations and rich birdlife, located within Ankara Province.
  • E. Kanık
    Kanık is the surname of the influential Turkish poet Orhan Veli Kanık, a leading figure in modern Turkish literature and the Garip movement.
  • 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_69bd43f3d6e08190a91824f833d51bbe completed March 20, 2026, 12:56 p.m.
NER Named-entity recognition batch_69bd57760f4481908f69ce82be63d7f8 completed March 20, 2026, 2:19 p.m.
NED1 Entity disambiguation (via context triple) batch_69becf8f926481908f6e1cf33fc79a04 completed March 21, 2026, 5:04 p.m.
Created at: March 20, 2026, 1:03 p.m.