Triple

T6007410
Position Surface form Disambiguated ID Type / Status
Subject Kyabobo National Park E133744 entity
Predicate country P26 FINISHED
Object Ghana E23760 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: Ghana | Statement: [Kyabobo National Park, country, Ghana]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Ghana
Context triple: [Kyabobo National Park, country, Ghana]
  • A. Ghana chosen
    Ghana is a West African nation known for being the first sub-Saharan African country to gain independence from colonial rule and for its stable democracy and rich cultural heritage.
  • B. Anyako, Ghana
    Anyako, Ghana is a small coastal town in the Volta Region known as the hometown of internationally acclaimed sculptor El Anatsui.
  • C. Côte d'Ivoire
    Côte d'Ivoire is a West African country on the Gulf of Guinea known for its cocoa production, diverse cultures, and economic prominence in the region.
  • D. 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.
  • E. Costa d’Oiro
    Costa d’Oiro is a scenic coastal area near Lagos in Portugal’s Algarve region, known for its golden cliffs, sheltered coves, and picturesque beaches.
  • 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_69c00872444c8190bfaf1739dcec765c completed March 22, 2026, 3:19 p.m.
NER Named-entity recognition batch_69c04f13d9908190a11d9bef8652db93 completed March 22, 2026, 8:20 p.m.
NED1 Entity disambiguation (via context triple) batch_69c5e3a5d54c8190b2bc8b3291f8ac2f completed March 27, 2026, 1:55 a.m.
Created at: March 22, 2026, 4:06 p.m.