Triple

T2874339
Position Surface form Disambiguated ID Type / Status
Subject Stevenage E56839 entity
Predicate hasTwinTown P919 FINISHED
Object Shymkent E51721 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: Shymkent | Statement: [Stevenage, hasTwinTown, Shymkent]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Shymkent
Context triple: [Stevenage, hasTwinTown, Shymkent]
  • A. Shymkent chosen
    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.
  • B. Almaty
    Almaty is the largest city and main commercial and cultural center of Kazakhstan, located in the country’s mountainous southeast.
  • C. Karaganda
    Karaganda is a large industrial city in central Kazakhstan known for its coal mining industry and Soviet-era history.
  • D. Pavlodar
    Pavlodar is a major industrial and cultural city in northeastern Kazakhstan, located on the Irtysh River.
  • E. Atyrau
    Atyrau is a city in western Kazakhstan located near the Caspian Sea, notable for straddling the boundary between Europe and Asia and serving as a major center for the country’s oil industry.
  • 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_69ab4a4ced288190ab6d3e062d10f7f6 completed March 6, 2026, 9:42 p.m.
NER Named-entity recognition batch_69abe0032ddc8190bb4d15ec7e3c63e8 completed March 7, 2026, 8:21 a.m.
NED1 Entity disambiguation (via context triple) batch_69b01db780908190919d859205464b2e completed March 10, 2026, 1:33 p.m.
Created at: March 6, 2026, 10:03 p.m.