Triple

T23001456
Position Surface form Disambiguated ID Type / Status
Subject Sakarya, Turkey E572641 entity
Predicate hasDistrict P459 FINISHED
Object Serdivan NE NERFINISHED

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: Serdivan | Statement: [Sakarya, Turkey, hasDistrict, Serdivan]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Serdivan
Context triple: [Sakarya, Turkey, hasDistrict, Serdivan]
  • A. Serdivan chosen
    Serdivan is a rapidly developing district and suburban area of the city of Sakarya in northwestern Turkey, known for its residential neighborhoods, university presence, and growing commercial centers.
  • B. Suşehri
    Suşehri is a town and district in northeastern Turkey known for its location within Sivas Province and its surrounding mountainous landscape.
  • C. Orhangazi
    Orhangazi is a town and district in northwestern Turkey known for its olive cultivation and location near Lake İznik in Bursa Province.
  • D. Gürbulak
    Gürbulak is a Turkish border village and crossing point on the frontier with Iran, serving as a key gateway between the two countries.
  • E. Нор-Баязет
    Нор-Баязет — это историческое название армянского города Гавар, расположенного в Гегаркуникской области у озера Севан.
  • F. None of above.
  • G. Unsure - the case is ambiguous/there is not enough information to decide.

Provenance (2 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_69e245b6a3ac81908087599eefe3e365 completed April 17, 2026, 2:37 p.m.
NER Named-entity recognition batch_69f18353d05481909abacb48a14ef21e completed April 29, 2026, 4:04 a.m.
Created at: April 17, 2026, 3:50 p.m.