Triple

T1925172
Position Surface form Disambiguated ID Type / Status
Subject Guinea E40812 entity
Predicate hasRegion P285 FINISHED
Object Lower Guinea E67981 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: Lower Guinea | Statement: [Guinea, hasRegion, Lower Guinea]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Lower Guinea
Context triple: [Guinea, hasRegion, Lower Guinea]
  • A. Lower Guinea chosen
    Lower Guinea is a coastal subregion of West Africa characterized by humid tropical forests, significant biodiversity, and important agricultural and port activities.
  • B. 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.
  • C. Cross River
    Cross River is a tributary stream in New York State that feeds the Cross River Reservoir and ultimately forms part of the New York City water supply system.
  • D. Congo
    Congo is a Central African country whose economy is heavily reliant on oil production and exports.
  • E. Volta River
    The Volta River is a major river system in West Africa that flows primarily through Ghana, where it feeds Lake Volta, one of the world’s largest artificial reservoirs.
  • 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_69a8864711648190b07bed24ed76258e completed March 4, 2026, 7:21 p.m.
NER Named-entity recognition batch_69abb260da088190ac53bfc9437e112b completed March 7, 2026, 5:06 a.m.
NED1 Entity disambiguation (via context triple) batch_69adf3e881748190b00f125185e91271 completed March 8, 2026, 10:10 p.m.
Created at: March 4, 2026, 7:35 p.m.