Triple

T20492171
Position Surface form Disambiguated ID Type / Status
Subject Gulf of İzmit E502771 entity
Predicate locatedNear P294 FINISHED
Object Gebze 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: Gebze | Statement: [Gulf of İzmit, locatedNear, Gebze]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Gebze
Context triple: [Gulf of İzmit, locatedNear, Gebze]
  • A. Gebze chosen
    Gebze is an industrial city in Turkey’s Kocaeli Province, located east of Istanbul and known as a major manufacturing and logistics hub in the Marmara region.
  • B. Halkalı
    Halkalı is a western district of Istanbul, Turkey, known as a major residential area and transport hub featuring significant rail and road connections.
  • C. Seydişehir
    Seydişehir is a town and district in central Turkey known for its aluminum industry and location within Konya Province.
  • D. Karacabey
    Karacabey is a town and district in northwestern Turkey known for its agriculture and proximity to both the Marmara Sea and the city of Bursa.
  • E. Ereğli
    Ereğli is a district and town in central Turkey known for its agricultural production and location within Konya Province on the Central Anatolian plateau.
  • 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_69e0b4b0373881909dd3e9387f82eab4 completed April 16, 2026, 10:06 a.m.
NER Named-entity recognition batch_69e69cba5b708190bef437acf6321b81 completed April 20, 2026, 9:38 p.m.
Created at: April 16, 2026, 11:35 a.m.