Triple

T8591326
Position Surface form Disambiguated ID Type / Status
Subject Nigerien security forces E203433 entity
Predicate operatesIn P82 FINISHED
Object Niger E22368 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: Niger | Statement: [Nigerien security forces, operatesIn, Niger]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Niger
Context triple: [Nigerien security forces, operatesIn, Niger]
  • A. Niger chosen
    Niger is a landlocked West African country in the Sahel region, known for its vast desert landscapes, uranium resources, and predominantly rural population.
  • B. Guinea
    Guinea is a West African country on the Atlantic coast known for its rich mineral resources, diverse ethnic groups, and role as a major producer of bauxite.
  • C. Mali
    Mali is a landlocked West African country known for its historic trading cities like Timbuktu, rich Sahelian culture, and significant role in the ancient Mali Empire.
  • D. Río de Oro
    Río de Oro is a river in northeastern Colombia that flows through the Santander region and passes near the city of Bucaramanga.
  • E. Río de Oro
    Río de Oro was a former Spanish colonial territory in northwest Africa that later became part of the disputed region of Western Sahara.
  • 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_69ca832a7f108190b4e4f5648abf4aa2 completed March 30, 2026, 2:05 p.m.
NER Named-entity recognition batch_69cc4665f1708190b736dd67593234d7 completed March 31, 2026, 10:10 p.m.
NED1 Entity disambiguation (via context triple) batch_69cebb9ef3ac819098810294e6bc34a7 completed April 2, 2026, 6:55 p.m.
Created at: March 30, 2026, 6:23 p.m.