Triple

T5357125
Position Surface form Disambiguated ID Type / Status
Subject Dessau E102721 entity
Predicate twinnedWith P1072 FINISHED
Object Rostov-on-Don E35707 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: Rostov-on-Don | Statement: [Dessau, twinnedWith, Rostov-on-Don]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Rostov-on-Don
Context triple: [Dessau, twinnedWith, Rostov-on-Don]
  • A. Rostov-on-Don chosen
    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.
  • B. Rostov
    Rostov is one of Russia’s oldest and most historically significant towns, renowned for its well-preserved kremlin and traditional architecture.
  • C. Rostova
    Rostova is a Russian surname best known from Leo Tolstoy’s novel "War and Peace," where it is borne by members of the central Rostov family.
  • D. 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.
  • E. Voronezh
    Voronezh is a major city in southwestern Russia, situated on the Voronezh River and serving as an important cultural, industrial, and transportation center.
  • 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_69bd43d8f7248190b64c140734b5c9a8 completed March 20, 2026, 12:55 p.m.
NER Named-entity recognition batch_69bd863099b081909d20f7014b98de5a completed March 20, 2026, 5:38 p.m.
NED1 Entity disambiguation (via context triple) batch_69c1351fb4a88190bb12f3a5f8cd92ac completed March 23, 2026, 12:42 p.m.
Created at: March 20, 2026, 2:01 p.m.