Triple

T5238789
Position Surface form Disambiguated ID Type / Status
Subject Kocaeli Province E118288 entity
Predicate hasCity P316 FINISHED
Object Gebze E216981 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: Gebze | Statement: [Kocaeli Province, hasCity, Gebze]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Gebze
Context triple: [Kocaeli Province, hasCity, 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. 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.
  • E. Ataşehir
    Ataşehir is a modern residential and business district on the Asian side of Istanbul, known for its high-rise developments and financial centers.
  • 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_69bd4467db0881909b3b0982df32cc8f completed March 20, 2026, 12:58 p.m.
NER Named-entity recognition batch_69bd7b290b88819095bc99c234260d25 completed March 20, 2026, 4:51 p.m.
NED1 Entity disambiguation (via context triple) batch_69bef823afd88190a3a41e7fff09d449 completed March 21, 2026, 7:57 p.m.
Created at: March 20, 2026, 1:49 p.m.