Triple

T8790363
Position Surface form Disambiguated ID Type / Status
Subject Poyrazköy E209146 entity
Predicate partOf P40 FINISHED
Object Province of Istanbul E182524 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: Province of Istanbul | Statement: [Poyrazköy, partOf, Province of Istanbul]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Province of Istanbul
Context triple: [Poyrazköy, partOf, Province of Istanbul]
  • A. Istanbul Province chosen
    Istanbul Province is a populous administrative region in northwestern Turkey that encompasses the historic city of Istanbul, spanning both Europe and Asia.
  • B. Osmaniye Province
    Osmaniye Province is a region in southern Turkey known for its agricultural economy, historical sites, and location near the Mediterranean coast.
  • C. Ankara Province
    Ankara Province is a central Anatolian administrative region of Turkey that includes and is centered around the national capital city, Ankara.
  • D. Hatay Province
    Hatay Province is a southern Turkish province on the Mediterranean coast, known for its multicultural heritage, ancient cities, and strategic location bordering Syria.
  • E. Antalya Province
    Antalya Province is a large Mediterranean coastal region in southwestern Turkey known for its major tourist resorts, beaches, and historical 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_69ca836168108190bb43d3dc235c1f55 completed March 30, 2026, 2:06 p.m.
NER Named-entity recognition batch_69cc5f8d25f881908863d636fa57a8a2 completed March 31, 2026, 11:58 p.m.
NED1 Entity disambiguation (via context triple) batch_69cfc921d3408190a2f823473bf9b4bc completed April 3, 2026, 2:05 p.m.
Created at: March 30, 2026, 6:43 p.m.