Triple

T7320476
Position Surface form Disambiguated ID Type / Status
Subject Balıkesir Province E168529 entity
Predicate containsCity P294 FINISHED
Object Ayvalık E524142 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: Ayvalık | Statement: [Balıkesir Province, containsCity, Ayvalık]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Ayvalık
Context triple: [Balıkesir Province, containsCity, Ayvalık]
  • A. Ayvalık chosen
    Ayvalık is a coastal town in northwestern Turkey known for its historic Greek architecture, olive oil production, and scenic Aegean Sea views.
  • B. Karaköy
    Karaköy is a historic waterfront neighborhood in Istanbul known for its bustling port, cafes, and mix of traditional and modern urban life.
  • C. Akyurt
    Akyurt is a district and rapidly developing suburban area of Ankara in central Turkey, known for its industrial zones and proximity to the capital’s airport.
  • D. Doğanhisar
    Doğanhisar is a rural district and town in central Turkey known for its agricultural economy and location within the Konya region.
  • E. Muratpaşa
    Muratpaşa is a central district and municipality of the city of Antalya in southern Turkey, known for its coastal location and urban, touristic character.
  • 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_69c68a5251508190ad68df4151cfeb04 completed March 27, 2026, 1:46 p.m.
NER Named-entity recognition batch_69c6ef1a7a3c81909504eb711056f302 completed March 27, 2026, 8:56 p.m.
NED1 Entity disambiguation (via context triple) batch_69c802ae19d88190a2f7997a6f3dfb1e completed March 28, 2026, 4:32 p.m.
Created at: March 27, 2026, 3:02 p.m.