Triple

T17466149
Position Surface form Disambiguated ID Type / Status
Subject Guinean mangroves E425282 entity
Predicate foundInCountry P846 FINISHED
Object Guinea 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: Guinea | Statement: [Guinean mangroves, foundInCountry, Guinea]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Guinea
Context triple: [Guinean mangroves, foundInCountry, 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. La Guinea
    La Guinea is a small settlement located on Isla del Rey in Spain’s Balearic Islands.
  • C. 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.
  • D. Gabon
    Gabon is a Central African country on the Atlantic coast, known for its equatorial rainforests, rich biodiversity, and significant oil reserves.
  • E. 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.
  • 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_69d889dbc2e88190b18ea6115e819258 completed April 10, 2026, 5:25 a.m.
NER Named-entity recognition batch_69e451a7e2a481908c32defa3401f848 completed April 19, 2026, 3:53 a.m.
Created at: April 10, 2026, 5:47 a.m.