Triple

T6275293
Position Surface form Disambiguated ID Type / Status
Subject Ecdat Park E140640 entity
Predicate locatedIn P40 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: [Ecdat Park, locatedIn, Konya]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Konya
Context triple: [Ecdat Park, locatedIn, 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_69c008cc158881908df6ec94a911c736 completed March 22, 2026, 3:20 p.m.
NER Named-entity recognition batch_69c063c170bc8190933e2fd5c9fef783 completed March 22, 2026, 9:48 p.m.
NED1 Entity disambiguation (via context triple) batch_69c70057abc48190a5855ce1c6029d81 completed March 27, 2026, 10:10 p.m.
Created at: March 22, 2026, 4:25 p.m.