Triple

T5086259
Position Surface form Disambiguated ID Type / Status
Subject Kaykaus I E114643 entity
Predicate capital P234 FINISHED
Object Konya E14759 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: Konya | Statement: [Kaykaus I, capital, Konya]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Konya
Context triple: [Kaykaus I, capital, Konya]
  • A. Konya chosen
    Konya is a major city in central Anatolia known for its rich Seljuk heritage and as the home of the Sufi mystic Rumi and the Whirling Dervishes.
  • B. Kayseri
    Kayseri is a historic city in central Turkey, known for its Seljuk and Ottoman architectural heritage and its role as a major commercial and cultural center in Anatolia.
  • C. Kütahya
    Kütahya is a historic city in western Turkey known for its Ottoman-era architecture and traditional ceramic and tile production.
  • D. Eskişehir
    Eskişehir is a major university and industrial city in northwestern Turkey, known for its vibrant student life, modern urban design, and rich cultural heritage.
  • E. Karabük
    Karabük is an industrial city in northern Turkey best known for its historic iron and steel industry and its proximity to the UNESCO-listed Ottoman town of Safranbolu.
  • 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_69bd443e941881908eb4e8c685b6f656 completed March 20, 2026, 12:57 p.m.
NER Named-entity recognition batch_69bd751db4f4819088b998d7af0e6f41 completed March 20, 2026, 4:26 p.m.
NED1 Entity disambiguation (via context triple) batch_69bfba1e755081909649e0dd8c4d2270 completed March 22, 2026, 9:45 a.m.
Created at: March 20, 2026, 1:40 p.m.