Triple

T7840491
Position Surface form Disambiguated ID Type / Status
Subject İzmir Province E181790 entity
Predicate contains P35 FINISHED
Object Seferihisar E629347 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: Seferihisar | Statement: [İzmir Province, contains, Seferihisar]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Seferihisar
Context triple: [İzmir Province, contains, Seferihisar]
  • A. Seferihisar chosen
    Seferihisar is a coastal town in Turkey’s İzmir Province, known as one of the country’s first officially designated “Cittaslow” (slow city) communities.
  • B. Şereflikoçhisar
    Şereflikoçhisar is a district and town in central Turkey known for its proximity to the vast Tuz Gölü (Salt Lake) and its salt production.
  • C. Afyonkarahisar
    Afyonkarahisar is a historic city in western Turkey known for its strategic location, thermal springs, and prominent rock fortress overlooking the urban center.
  • D. Sancaktepe
    Sancaktepe is a rapidly developing residential district located on the Asian side of Istanbul, Turkey.
  • E. Kemalpaşa
    Kemalpaşa is a district and town in western Turkey known for its cherry production and proximity to the city of İzmir.
  • 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_69ca8285d6488190a95d4c02d7354b53 completed March 30, 2026, 2:02 p.m.
NER Named-entity recognition batch_69cb14c589748190b34d0911d373e194 completed March 31, 2026, 12:26 a.m.
NED1 Entity disambiguation (via context triple) batch_69cd66ecea6c819097a74513c5d84193 completed April 1, 2026, 6:41 p.m.
Created at: March 30, 2026, 4:47 p.m.