Triple

T2623400
Position Surface form Disambiguated ID Type / Status
Subject Don Army E59060 entity
Predicate headquartersLocation P62 FINISHED
Object Novocherkassk E217917 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: Novocherkassk | Statement: [Don Army, headquartersLocation, Novocherkassk]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Novocherkassk
Context triple: [Don Army, headquartersLocation, Novocherkassk]
  • A. Novocherkassk chosen
    Novocherkassk is a historic city in Russia’s Rostov Oblast that served as a key Cossack and military administrative center.
  • B. Rostov-on-Don
    Rostov-on-Don is a major port city in southern Russia, located on the Don River near the Sea of Azov and serving as an important administrative, cultural, and industrial center of the region.
  • C. Volgograd
    Volgograd is a major city in southwestern Russia on the Volga River, historically known as Stalingrad and renowned as the site of one of World War II’s most pivotal and brutal battles.
  • D. Stavropol
    Stavropol is a major administrative, cultural, and economic center in southwestern Russia, serving as the capital of Stavropol Krai in the North Caucasus region.
  • E. Berdyansk
    Berdyansk is a port city in southeastern Ukraine on the northern coast of the Sea of Azov, known for its maritime trade, beaches, and resort facilities.
  • 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_69ab4ac558388190962492cd2e1b0ce6 completed March 6, 2026, 9:44 p.m.
NER Named-entity recognition batch_69abd8af06fc8190ab48d746b8c8892b completed March 7, 2026, 7:50 a.m.
NED1 Entity disambiguation (via context triple) batch_69b54c16c05481908f451b492ca9f47f completed March 14, 2026, 11:52 a.m.
Created at: March 6, 2026, 9:50 p.m.