Triple

T4935535
Position Surface form Disambiguated ID Type / Status
Subject Namangan E110802 entity
Predicate capitalOf P204 FINISHED
Object Namangan Region E110802 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: Namangan Region | Statement: [Namangan, capitalOf, Namangan Region]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Namangan Region
Context triple: [Namangan, capitalOf, Namangan Region]
  • A. Andijan Region
    Andijan Region is an administrative region in eastern Uzbekistan known for its dense population, fertile Fergana Valley agriculture, and the city of Andijan as its capital.
  • B. Namangan chosen
    Namangan is a major city in eastern Uzbekistan, known as an important cultural and economic center in the Fergana Valley.
  • C. Jalal-Abad Region
    Jalal-Abad Region is an administrative region in western Kyrgyzstan known for its mountainous landscapes, river valleys, and significant agricultural and hydropower resources.
  • D. Daşoguz Region
    Daşoguz Region is an administrative region in northern Turkmenistan known for its desert landscapes and proximity to the historical Khorezm area.
  • E. Atyrau Region
    Atyrau Region is a western Kazakhstani administrative area located along the northern Caspian Sea, known for its oil and gas industry and low-lying Caspian Depression landscapes.
  • 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_69bd4415eee08190bdce70276e56a5b4 completed March 20, 2026, 12:56 p.m.
NER Named-entity recognition batch_69bd706825188190b854dca5ca2f9db6 completed March 20, 2026, 4:06 p.m.
NED1 Entity disambiguation (via context triple) batch_69be77b74c748190a995a26f45b79ee9 completed March 21, 2026, 10:49 a.m.
Created at: March 20, 2026, 1:30 p.m.