Triple

T688254
Position Surface form Disambiguated ID Type / Status
Subject Bursa E13331 entity
Predicate partOf P40 FINISHED
Object Marmara industrial corridor E31349 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: Marmara industrial corridor | Statement: [Bursa, partOf, Marmara industrial corridor]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Marmara industrial corridor
Context triple: [Bursa, partOf, Marmara industrial corridor]
  • A. Marmara Region chosen
    The Marmara Region is a northwestern area of Turkey that includes Istanbul and serves as a major economic, industrial, and transportation hub connecting Europe and Asia.
  • B. Ankara Metro
    Ankara Metro is the rapid transit system serving Turkey's capital city, providing urban rail transportation across Ankara and its surrounding districts.
  • C. Izmir Metro
    Izmir Metro is a rapid transit rail system serving the city of Izmir, Turkey, providing high-capacity urban transportation across key districts.
  • 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. Balkanabat
    Balkanabat is a significant urban and administrative center in western Turkmenistan, known for serving as a regional hub for the country's oil and gas 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_69a4933e0f98819097d22766c49b61b8 completed March 1, 2026, 7:27 p.m.
NER Named-entity recognition batch_69a4a0953fb481909e1d4177ee191351 completed March 1, 2026, 8:24 p.m.
NED1 Entity disambiguation (via context triple) batch_69a5dca352248190a3e1b4e4c58a1e7f completed March 2, 2026, 6:53 p.m.
Created at: March 1, 2026, 7:36 p.m.