Triple

T18987014
Position Surface form Disambiguated ID Type / Status
Subject Zhetysu E464581 entity
Predicate hasMajorCity P316 FINISHED
Object Almaty 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: Almaty | Statement: [Zhetysu, hasMajorCity, Almaty]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Almaty
Context triple: [Zhetysu, hasMajorCity, Almaty]
  • A. Almaty chosen
    Almaty is the largest city and main commercial and cultural center of Kazakhstan, located in the country’s mountainous southeast.
  • B. Karaganda
    Karaganda is a large industrial city in central Kazakhstan known for its coal mining industry and Soviet-era history.
  • C. Shymkent
    Shymkent is one of the largest and most populous cities in southern Kazakhstan, serving as a key industrial, commercial, and cultural center of the region.
  • D. Nur-Sultan
    Nur-Sultan is the planned capital city of Kazakhstan, known for its rapid modern development and distinctive futuristic architecture.
  • E. Zhezkazgan
    Zhezkazgan is a major industrial and mining city in central Kazakhstan, known especially for its large copper deposits and metallurgical complex.
  • 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_69d8dd008af48190a97ff1c6488edf1b completed April 10, 2026, 11:20 a.m.
NER Named-entity recognition batch_69e5d660835c8190bedd78590b3e0a7e completed April 20, 2026, 7:31 a.m.
Created at: April 10, 2026, 12:01 p.m.