Triple

T118220
Position Surface form Disambiguated ID Type / Status
Subject Strasbourg E2388 entity
Predicate twinCity P1072 FINISHED
Object Stavropol E26125 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: Stavropol | Statement: [Strasbourg, twinCity, Stavropol]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Stavropol
Context triple: [Strasbourg, twinCity, Stavropol]
  • A. 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.
  • B. Stavropol Krai chosen
    Stavropol Krai is a federal subject in southwestern Russia in the North Caucasus region, known for its diverse population, agricultural importance, and role as a historical home to various ethnic communities.
  • C. Krasnodar Krai
    Krasnodar Krai is a federal subject of southwestern Russia on the Black Sea and Azov Sea coasts, known for its diverse population, agriculture, and resort cities such as Sochi.
  • D. Moscow Oblast
    Moscow Oblast is a federal subject of Russia that surrounds, but does not include, the city of Moscow and serves as a major industrial and population center in western Russia.
  • E. Simferopol
    Simferopol is the administrative and cultural center of Crimea, known as a key regional hub for transportation, education, and 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_69a2506c5428819085c28a8884790e29 completed Feb. 28, 2026, 2:18 a.m.
NER Named-entity recognition batch_69a257145e0c81908a00c6c4a17b53f0 completed Feb. 28, 2026, 2:46 a.m.
NED1 Entity disambiguation (via context triple) batch_69a32bc3efbc8190831cb527c122ac59 completed Feb. 28, 2026, 5:54 p.m.
Created at: Feb. 28, 2026, 2:24 a.m.