Triple

T7141740
Position Surface form Disambiguated ID Type / Status
Subject Tekirdağ Province E166458 entity
Predicate hasCity P316 FINISHED
Object Şarköy
Şarköy is a coastal town and district in northwestern Turkey, known for its beaches, vineyards, and wine production along the Sea of Marmara.
 E644679 NE FINISHED

How this triple was built (4 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: Şarköy | Statement: [Tekirdağ Province, hasCity, Şarköy]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07 
Target entity: Şarköy
Context triple: [Tekirdağ Province, hasCity, Şarköy]
  • A. Şirinköy
    Şirinköy is a village located on Gökçeada, Turkey’s largest Aegean island in the Çanakkale Province.
  • B. Dereköy
    Dereköy is a village on the Aegean island of Gökçeada (historically known as Imbros/İmroz) in Turkey, noted for its traditional stone houses and Greek heritage.
  • C. Karaköy
    Karaköy is a historic waterfront neighborhood in Istanbul known for its bustling port, cafes, and mix of traditional and modern urban life.
  • D. 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.
  • E. Torbalı
    Torbalı is a district and rapidly growing suburban area of İzmir, Turkey, known for its industrial zones and connection to the city via the İZBAN commuter rail system.
  • F. None of above. chosen
  • G. Unsure - the case is ambiguous/there is not enough information to decide.
NEDg Description generation gpt-5.1
Instruction
Generate a one-sentence description of the target entity. 
You are given a context triple in the form (subject, predicate, object), where the object is the target entity. 
# Instructions
Use the triple to infer relevant information about the entity. Describe the entity based on what is most defining, well-known. 
Avoid repeating the information from the triple, unless really essential.
# Response Format
Return only the sentence: "Description: [one-sentence description of the target entity]"
Input
Entity: Şarköy
Triple: [Tekirdağ Province, hasCity, Şarköy]
Generated description
Şarköy is a coastal town and district in northwestern Turkey, known for its beaches, vineyards, and wine production along the Sea of Marmara.
NED2 Entity disambiguation (via description) gpt-5-mini-2025-08-07 
Target entity: Şarköy
Target entity description: Şarköy is a coastal town and district in northwestern Turkey, known for its beaches, vineyards, and wine production along the Sea of Marmara.
  • A. Şirinköy
    Şirinköy is a village located on Gökçeada, Turkey’s largest Aegean island in the Çanakkale Province.
  • B. Dereköy
    Dereköy is a village on the Aegean island of Gökçeada (historically known as Imbros/İmroz) in Turkey, noted for its traditional stone houses and Greek heritage.
  • C. Karaköy
    Karaköy is a historic waterfront neighborhood in Istanbul known for its bustling port, cafes, and mix of traditional and modern urban life.
  • D. 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.
  • E. Torbalı
    Torbalı is a district and rapidly growing suburban area of İzmir, Turkey, known for its industrial zones and connection to the city via the İZBAN commuter rail system.
  • F. None of above. chosen

Provenance (5 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_69c6888579d481909e05a8d6b81bf733 completed March 27, 2026, 1:39 p.m.
NER Named-entity recognition batch_69c6e778875c8190a5202d3efe5a842d completed March 27, 2026, 8:24 p.m.
NED1 Entity disambiguation (via context triple) batch_69c7a3502ed88190ac378a93891c8d9e completed March 28, 2026, 9:45 a.m.
NEDg Description generation batch_69c7a45e81bc8190bf4c47e3bb5fe077 completed March 28, 2026, 9:50 a.m.
NED2 Entity disambiguation (via description) batch_69c7a4f074708190a5ce0a863ffd4f25 completed March 28, 2026, 9:52 a.m.
Created at: March 27, 2026, 2:45 p.m.