Triple

T16829470
Position Surface form Disambiguated ID Type / Status
Subject San Stefano E409109 entity
Predicate modernNameOfArea P74746 FINISHED
Object Yeşilköy E1235419 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: Yeşilköy | Statement: [San Stefano, modernNameOfArea, Yeşilköy]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Yeşilköy
Context triple: [San Stefano, modernNameOfArea, Yeşilköy]
  • A. Yeşilköy chosen
    Yeşilköy is a coastal neighborhood of Istanbul, Turkey, historically known as Ayastefanos and notable as the site where the 1878 Treaty of San Stefano was signed.
  • B. Şirinköy
    Şirinköy is a village located on Gökçeada, Turkey’s largest Aegean island in the Çanakkale Province.
  • C. Poyrazköy
    Poyrazköy is a coastal neighborhood on the Asian side of Istanbul, Turkey, situated at the northern entrance of the Bosphorus Strait.
  • D. Yeşilyurt
    Yeşilyurt is a district and municipality in eastern Turkey, located within Malatya Province and known for its agricultural production and growing urban development.
  • E. Yalıköy
    Yalıköy is a neighborhood in the Beykoz district of Istanbul, Turkey, known for its residential character and proximity to the Bosphorus.
  • 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_69d88394566c8190b3dcbdc72935f7fa completed April 10, 2026, 4:59 a.m.
NER Named-entity recognition batch_69e3b315dbbc81908a1c83069e058770 completed April 18, 2026, 4:36 p.m.
NED1 Entity disambiguation (via context triple) batch_6a00bb13ec908190853627066fb2c492 completed May 10, 2026, 5:06 p.m.
Created at: April 10, 2026, 5:23 a.m.