Triple

T20766963
Position Surface form Disambiguated ID Type / Status
Subject Aleksei Kaledin E511121 entity
Predicate regionOfActivity P82 FINISHED
Object Don region NE NERFINISHED

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: [Aleksei Kaledin, regionOfActivity, Don region]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Don region
Context triple: [Aleksei Kaledin, regionOfActivity, 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. Trièves region
    The Trièves region is a rural area in the French Prealps known for its dramatic mountain scenery, traditional villages, and outdoor recreation opportunities.
  • C. La Mé Region
    La Mé Region is an administrative region in southeastern Ivory Coast, known for its agricultural activities and inclusion within the larger Lagunes District.
  • D. Vivarais region
    The Vivarais region is a historic area in south-central France, largely corresponding to part of the Ardèche department, known for its rugged landscapes, vineyards, and river valleys.
  • E. San-Pédro Region
    San-Pédro Region is an administrative region in southwestern Ivory Coast known for its major port city of San-Pédro and its role in the country’s cocoa and timber industries.
  • F. None of above.
  • G. Unsure - the case is ambiguous/there is not enough information to decide.

Provenance (2 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_69e0b4ca01148190ac018e57e0cab46f completed April 16, 2026, 10:07 a.m.
NER Named-entity recognition batch_69e6c24ceab8819094e331c57abe6879 completed April 21, 2026, 12:18 a.m.
Created at: April 16, 2026, 12:36 p.m.