Triple

T11264205
Position Surface form Disambiguated ID Type / Status
Subject Aralsk E266641 entity
Predicate partOf P40 FINISHED
Object Aral District E921151 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: Aral District | Statement: [Aralsk, partOf, Aral District]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Aral District
Context triple: [Aralsk, partOf, Aral District]
  • A. Aral District chosen
    Aral District is an administrative district in Kazakhstan situated near the northern Aral Sea, known for encompassing areas affected by the sea’s environmental decline and related restoration efforts.
  • B. Saryagash District
    Saryagash District is an administrative district in southern Kazakhstan known for its proximity to the Uzbek border and its mineral springs.
  • C. Yasamal District
    Yasamal District is a central administrative district of Baku, Azerbaijan, known for its dense urban development, residential neighborhoods, and key cultural and educational institutions.
  • D. Urgun District
    Urgun District is an administrative district in southeastern Afghanistan known for its strategic location and role within Paktika Province.
  • E. Nurgal District
    Nurgal District is an administrative district located in Kunar Province in eastern Afghanistan.
  • 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_69d6aac7953c8190b82caf9d7640fdf9 completed April 8, 2026, 7:21 p.m.
NER Named-entity recognition batch_69d7e94d56048190bf808e1bc2188714 completed April 9, 2026, 6 p.m.
NED1 Entity disambiguation (via context triple) batch_69e5b7b051988190abec04740df75c89 completed April 20, 2026, 5:20 a.m.
Created at: April 8, 2026, 9:31 p.m.