Triple

T2623392
Position Surface form Disambiguated ID Type / Status
Subject Don Army E59060 entity
Predicate region P40 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: [Don Army, region, Don region]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Don region
Context triple: [Don Army, region, 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_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_69af909b7d9881908930a98d004998fb completed March 10, 2026, 3:31 a.m.
Created at: March 6, 2026, 9:50 p.m.