Triple

T7862174
Position Surface form Disambiguated ID Type / Status
Subject Istanbul Province E182524 entity
Predicate hasDistrict P459 FINISHED
Object Arnavutköy E238391 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: Arnavutköy | Statement: [Istanbul Province, hasDistrict, Arnavutköy]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Arnavutköy
Context triple: [Istanbul Province, hasDistrict, Arnavutköy]
  • A. Arnavutköy chosen
    Arnavutköy is a district on the European side of Istanbul, Turkey, known for its rapidly developing urban areas and hosting the city’s main international airport.
  • B. Bayındır
    Bayındır is a town and district in western Turkey known for its agricultural production and location within İzmir Province.
  • C. Ayvacık
    Ayvacık is a small town and district in Turkey’s Çanakkale Province, known for its traditional stone houses and proximity to the Aegean coast and ancient sites like Assos.
  • D. Florya
    Florya is a coastal neighborhood in Istanbul, Turkey, known for its residential areas, seaside promenade, and recreational facilities.
  • E. Güzelyurt
    Güzelyurt is a town in the northwestern part of Cyprus, known for its citrus orchards and archaeological sites.
  • 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_69ca82887fd48190975896bf38c4596b completed March 30, 2026, 2:02 p.m.
NER Named-entity recognition batch_69cb36be5f408190b82a097b0825c57a completed March 31, 2026, 2:51 a.m.
NED1 Entity disambiguation (via context triple) batch_69cd9423b4608190acbe4a3141890a05 completed April 1, 2026, 9:54 p.m.
Created at: March 30, 2026, 4:53 p.m.