Triple

T7223642
Position Surface form Disambiguated ID Type / Status
Subject N'Ko script E150322 entity
Predicate usedInCountry P715 FINISHED
Object Guinea E40812 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: Guinea | Statement: [N'Ko script, usedInCountry, Guinea]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Guinea
Context triple: [N'Ko script, usedInCountry, Guinea]
  • A. Guinea chosen
    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.
  • B. Gaboni
    Gaboni is a small locality in southern Poland situated near the Beskid Sądecki mountain range, serving as a starting point for hikes to nearby peaks such as Przehyba.
  • C. Gabon
    Gabon is a Central African country on the Atlantic coast, known for its equatorial rainforests, rich biodiversity, and significant oil reserves.
  • D. The Gambia
    The Gambia is a small West African country centered around the Gambia River, known for its diverse ecosystems, colonial history, and tourism-focused economy.
  • E. Senegal
    Senegal is a West African country on the Atlantic coast known for its vibrant culture, historic role in transatlantic trade, and diverse coastal and Sahelian landscapes.
  • 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_69c687effb44819092b95d07d0368c9f completed March 27, 2026, 1:36 p.m.
NER Named-entity recognition batch_69c6e9b54a5c8190a4a289f32853a8fe completed March 27, 2026, 8:33 p.m.
NED1 Entity disambiguation (via context triple) batch_69c7d37833ec819084035e07fc35198b completed March 28, 2026, 1:11 p.m.
Created at: March 27, 2026, 2:54 p.m.