Triple

T20580815
Position Surface form Disambiguated ID Type / Status
Subject Kartepe E505648 entity
Predicate locatedNear P294 FINISHED
Object İzmit NE NERFINISHED

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: İzmit | Statement: [Kartepe, locatedNear, İzmit]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: İzmit
Context triple: [Kartepe, locatedNear, İzmit]
  • A. İzmit chosen
    İzmit is a city in northwestern Turkey on the Gulf of İzmit, historically significant as the site of ancient Nicomedia and an important industrial and transportation hub near Istanbul.
  • B. 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.
  • C. Adapazarı
    Adapazarı is a city in northwestern Turkey that serves as the administrative center of Sakarya Province and is known for its agricultural production and regional commerce.
  • D. Izmir
    Izmir is a major Turkish coastal city known as an important commercial and cultural hub on the Aegean Sea.
  • E. Samsun
    Samsun is a major Turkish port city on the Black Sea coast, known as an important regional hub for maritime trade and industry.
  • F. None of above.
  • G. Unsure - the case is ambiguous/there is not enough information to decide.

Provenance (2 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_69e0b4b9669c8190b8e81fc72817d42c completed April 16, 2026, 10:06 a.m.
NER Named-entity recognition batch_69e6a90e98a88190b5cb077973f97e68 completed April 20, 2026, 10:30 p.m.
Created at: April 16, 2026, 11:39 a.m.