Triple

T15113753
Position Surface form Disambiguated ID Type / Status
Subject Ngas E360980 entity
Predicate historicalRegion P915 FINISHED
Object Jos Plateau E289553 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: Jos Plateau | Statement: [Ngas, historicalRegion, Jos Plateau]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Jos Plateau
Context triple: [Ngas, historicalRegion, Jos Plateau]
  • A. Jos Plateau chosen
    Jos Plateau is a highland region in central Nigeria known for its cool climate, scenic landscapes, and rich mineral resources, especially tin.
  • B. Cézallier plateau
    The Cézallier plateau is a high-altitude volcanic and pastoral landscape in central France, known for its wide open grasslands, lakes, and traditional cattle farming.
  • C. Langres Plateau
    The Langres Plateau is a high limestone upland in northeastern France known as a major watershed that gives rise to several important rivers, including the Seine.
  • D. Montmorency plateau
    The Montmorency plateau is a raised geographic area in the Val-d'Oise department of northern France, known for its suburban communities overlooking the Paris metropolitan region.
  • E. Vesoul Plateau
    The Vesoul Plateau is a limestone upland region in eastern France characterized by rolling agricultural landscapes and small rural communities.
  • 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_69d85a0491ec8190830960be8fafb994 completed April 10, 2026, 2:01 a.m.
NER Named-entity recognition batch_69e0058f4fb88190a3d446a466aebcf1 completed April 15, 2026, 9:39 p.m.
NED1 Entity disambiguation (via context triple) batch_69febfe2369881908c7ebbad412d9000 completed May 9, 2026, 5:02 a.m.
Created at: April 10, 2026, 3:05 a.m.