Triple

T17473200
Position Surface form Disambiguated ID Type / Status
Subject Kars Province E425470 entity
Predicate contains P35 FINISHED
Object Kağızman district 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: Kağızman district | Statement: [Kars Province, contains, Kağızman district]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Kağızman district
Context triple: [Kars Province, contains, Kağızman district]
  • A. Kağızman District chosen
    Kağızman District is an administrative district in Kars Province in eastern Turkey, centered around the town of Kağızman.
  • B. Kağıthane district
    Kağıthane district is an urban area on the European side of Istanbul, Turkey, known for its rapid modernization and mixed residential and commercial neighborhoods.
  • C. Konak district
    Konak district is the central urban and administrative heart of İzmir, Turkey, known for its historic landmarks, bustling waterfront, and role as the city’s main commercial and cultural hub.
  • D. Bayrampaşa district
    Bayrampaşa district is a densely populated working- and middle-class district on the European side of Istanbul, known for its industrial areas, major transport hubs, and large bus terminal.
  • E. Sancaktepe district
    Sancaktepe district is a rapidly developing residential area on Istanbul’s Asian side, known for its growing infrastructure and improved connectivity to the city center.
  • 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_69d889dbc2e88190b18ea6115e819258 completed April 10, 2026, 5:25 a.m.
NER Named-entity recognition batch_69e451b990848190b2e8510d67e94b79 completed April 19, 2026, 3:53 a.m.
Created at: April 10, 2026, 5:47 a.m.