Triple

T9055346
Position Surface form Disambiguated ID Type / Status
Subject Gebze E216981 entity
Predicate locatedNear P294 FINISHED
Object İzmit E117800 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: İzmit | Statement: [Gebze, locatedNear, İzmit]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: İzmit
Context triple: [Gebze, 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 (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_69ca83d4425481909a319dab847724ec completed March 30, 2026, 2:08 p.m.
NER Named-entity recognition batch_69cc7a7488188190b3dd6bc2f2377503 completed April 1, 2026, 1:52 a.m.
NED1 Entity disambiguation (via context triple) batch_69d178be71188190bb9bdb719dd4d12d completed April 4, 2026, 8:46 p.m.
Created at: March 30, 2026, 7:10 p.m.