Triple

T15852165
Position Surface form Disambiguated ID Type / Status
Subject northwestern Turkey E384366 entity
Predicate hasMajorPort P942 FINISHED
Object Bandırma E553406 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: Bandırma | Statement: [northwestern Turkey, hasMajorPort, Bandırma]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Bandırma
Context triple: [northwestern Turkey, hasMajorPort, Bandırma]
  • A. Bandırma chosen
    Bandırma is a coastal city in northwestern Turkey on the Sea of Marmara, known as an important regional hub for maritime trade, industry, and transportation.
  • B. Samsun
    Samsun is a major Turkish port city on the Black Sea coast, known as an important regional hub for maritime trade and industry.
  • C. Mecidiye
    Mecidiye is the former Ottoman-era name of the Romanian city now known as Medgidia, located in the Dobruja region.
  • D. Trabzon
    Trabzon is a historic city in northeastern Turkey that serves as a major Black Sea port and regional cultural and commercial center.
  • E. Bursa
    Bursa is a major city in northwestern Turkey known historically as the first capital of the Ottoman Empire and today as an important industrial and cultural center.
  • 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_69d86da422088190aac39e32e6c68429 completed April 10, 2026, 3:25 a.m.
NER Named-entity recognition batch_69e14caddd2c8190859b2926b0e1ad35 completed April 16, 2026, 8:55 p.m.
NED1 Entity disambiguation (via context triple) batch_69ffa147bce481909fb6f6ef2793a5a8 completed May 9, 2026, 9:04 p.m.
Created at: April 10, 2026, 4:50 a.m.