Triple

T13266233
Position Surface form Disambiguated ID Type / Status
Subject Aydın Province E315931 entity
Predicate containsDistrict P22582 FINISHED
Object Kuşadası E410825 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: Kuşadası | Statement: [Aydın Province, containsDistrict, Kuşadası]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Kuşadası
Context triple: [Aydın Province, containsDistrict, Kuşadası]
  • A. Kuşadası chosen
    Kuşadası is a popular Aegean coastal resort town in western Turkey, known for its beaches, cruise port, and proximity to the ancient city of Ephesus.
  • B. Kekova
    Kekova is a small Turkish Mediterranean island and surrounding region famed for its submerged ancient ruins and scenic coastal landscape.
  • C. Çamlıyayla
    Çamlıyayla is a mountainous district and town in southern Turkey known for its cool highland climate and natural scenery.
  • D. Kuruçeşme
    Kuruçeşme is a Bosphorus-side neighborhood in Istanbul known for its waterfront parks, nightlife venues, and views of the strait.
  • E. Büyükada
    Büyükada is the largest and most popular of Istanbul’s Princes' Islands, known for its historic wooden mansions, car-free streets, and seaside promenades.
  • 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_69d806b1d9ac8190852c5571d5bd5f0f completed April 9, 2026, 8:06 p.m.
NER Named-entity recognition batch_69d9901e44bc8190966f87ae219d6bf4 completed April 11, 2026, 12:04 a.m.
NED1 Entity disambiguation (via context triple) batch_69f70a4ad79c8190b1304942dc48c0ff completed May 3, 2026, 8:41 a.m.
Created at: April 9, 2026, 9:25 p.m.