Triple

T3338991
Position Surface form Disambiguated ID Type / Status
Subject Pyotr Krasnov E70211 entity
Predicate residence P75 FINISHED
Object Don region E229102 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: Don region | Statement: [Pyotr Krasnov, residence, Don region]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Don region
Context triple: [Pyotr Krasnov, residence, Don region]
  • A. Don region chosen
    The Don region is a historical area in southern Russia centered around the Don River, traditionally associated with the homeland of the Don Cossacks.
  • B. Choiseul region
    The Choiseul region is an area of the Solomon Islands centered on Choiseul Island, known for its indigenous communities and use of Northwest Solomonic languages.
  • C. Dombes
    Dombes is a historic rural region in eastern France known for its many ponds, wetlands, and traditional fish farming.
  • D. Oriente region
    The Oriente region is a historical area in eastern Cuba known for its mountainous terrain, rich Afro-Cuban culture, and key role in the Cuban Revolution.
  • E. Dakar Region
    Dakar Region is the smallest yet most densely populated administrative region of Senegal, encompassing the nation’s capital and serving as its primary political, economic, and cultural hub.
  • 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_69ad85a405e48190b6e68de7cf9f319e completed March 8, 2026, 2:20 p.m.
NER Named-entity recognition batch_69adb1bd6c7c8190b7229de1433d8d20 completed March 8, 2026, 5:28 p.m.
NED1 Entity disambiguation (via context triple) batch_69b31a8ccc408190bae65d2d1a4d77bd completed March 12, 2026, 7:57 p.m.
Created at: March 8, 2026, 3:12 p.m.