Triple

T1453688
Position Surface form Disambiguated ID Type / Status
Subject Marmara Region E31349 entity
Predicate includesCity P3207 FINISHED
Object Yalova E60878 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: Yalova | Statement: [Marmara Region, includesCity, Yalova]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Yalova
Context triple: [Marmara Region, includesCity, Yalova]
  • A. Yalova chosen
    Yalova is a small coastal city in northwestern Turkey, known for its thermal springs, seaside promenade, and proximity to Istanbul across the Sea of Marmara.
  • B. Beykoz
    Beykoz is a green, waterfront district of Istanbul known for its forests, historic waterfront mansions, and scenic views along the Bosphorus.
  • C. Sarıyer
    Sarıyer is a district on the European side of Istanbul, Turkey, known for its Bosphorus coastline, historic neighborhoods, and prominent sports and educational institutions.
  • D. Çekmeköy
    Çekmeköy is a residential district on the Asian side of Istanbul, known for its rapidly developing housing areas and proximity to forested green spaces.
  • E. Üsküdar
    Üsküdar is a historic and densely populated district of Istanbul known for its waterfront along the Bosphorus, Ottoman-era mosques, and traditional neighborhoods.
  • 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_69a499171a28819085b993a3ac78e363 completed March 1, 2026, 7:52 p.m.
NER Named-entity recognition batch_69a4c57e82d48190a30a4512f39f5de0 completed March 1, 2026, 11:02 p.m.
NED1 Entity disambiguation (via context triple) batch_69adfb8d636c8190a8a9ca29d8a6fd82 completed March 8, 2026, 10:43 p.m.
Created at: March 1, 2026, 8 p.m.