Triple

T17071058
Position Surface form Disambiguated ID Type / Status
Subject TR-25 E414218 entity
Predicate regionName P2356 FINISHED
Object Erzurum 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: Erzurum | Statement: [TR-25, regionName, Erzurum]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Erzurum
Context triple: [TR-25, regionName, Erzurum]
  • A. Erzurum chosen
    Erzurum is a major city in eastern Turkey known for its historical architecture, harsh winters, and status as a regional cultural and economic center.
  • B. Elazığ
    Elazığ is a city in eastern Turkey known as a regional center near the Euphrates River and the Keban Dam, with a history shaped by both ancient civilizations and modern development.
  • C. Diyarbekir
    Diyarbekir is a historic city in southeastern Turkey, widely known today as Diyarbakır and notable for its ancient basalt city walls and rich Kurdish and Ottoman heritage.
  • D. Sivas
    Sivas is a historic city in central Turkey that served as an important political, commercial, and cultural center in Anatolia, especially during the Seljuk and Ottoman periods.
  • E. Karabük
    Karabük is an industrial city in northern Turkey best known for its historic iron and steel industry and its proximity to the UNESCO-listed Ottoman town of Safranbolu.
  • 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_69d886cef44c8190ba56c44b4e863e64 completed April 10, 2026, 5:12 a.m.
NER Named-entity recognition batch_69e3dbc0982c8190916f9905ddb5e575 completed April 18, 2026, 7:30 p.m.
Created at: April 10, 2026, 5:34 a.m.