Triple

T7175445
Position Surface form Disambiguated ID Type / Status
Subject Sakarya E167306 entity
Predicate nearbyCity P350 FINISHED
Object Duzce E598623 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: Duzce | Statement: [Sakarya, nearbyCity, Duzce]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Duzce
Context triple: [Sakarya, nearbyCity, Duzce]
  • A. Düzce chosen
    Düzce is a city in northwestern Turkey known for its location between Istanbul and Ankara and its proximity to the Black Sea.
  • B. Darıca
    Darıca is a coastal town and district in northwestern Turkey, situated on the Sea of Marmara and known for its zoo, recreation areas, and proximity to Istanbul.
  • C. Zonguldak
    Zonguldak is a port city on Turkey’s Black Sea coast known historically for its coal mining industry.
  • D. Bilecik
    Bilecik is a small city in northwestern Turkey known as the capital of Bilecik Province and for its proximity to the historic town of Söğüt, birthplace of the Ottoman Empire.
  • E. Muratlı
    Muratlı is a town and district in Turkey’s Thrace region, located within Tekirdağ Province and known for its agricultural and industrial activities.
  • 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_69c68889a2748190a316c5e65360361a completed March 27, 2026, 1:39 p.m.
NER Named-entity recognition batch_69c6e88ec6a8819083cbc3f4c39b8c79 completed March 27, 2026, 8:29 p.m.
NED1 Entity disambiguation (via context triple) batch_69c7d37cfb8c8190a788dcaa1080fb0b completed March 28, 2026, 1:11 p.m.
Created at: March 27, 2026, 2:48 p.m.