Triple

T16339433
Position Surface form Disambiguated ID Type / Status
Subject Mwalimu E396757 entity
Predicate usedInCountry P715 FINISHED
Object Tanzania E19037 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: Tanzania | Statement: [Mwalimu, usedInCountry, Tanzania]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Tanzania
Context triple: [Mwalimu, usedInCountry, Tanzania]
  • A. Tanzania chosen
    Tanzania is an East African nation known for its vast wilderness areas, including the Serengeti National Park and Mount Kilimanjaro, as well as its rich cultural diversity.
  • B. Tansaniaweg
    Tansaniaweg is a street in Berlin’s Afrikanisches Viertel, named in reference to the East African country Tanzania and its historical connections to Germany.
  • C. Mozambique
    Mozambique is a southeastern African nation on the Indian Ocean known for its Portuguese colonial heritage, rich cultural diversity, and extensive coastline with important ports and marine resources.
  • D. Tanzania and Burundi
    Tanzania and Burundi are neighboring East African countries that share a border along the eastern shore of Lake Tanganyika.
  • E. Malawi
    Malawi is a landlocked country in southeastern Africa known for Lake Malawi, its predominantly agricultural economy, and membership in regional and international organizations including the Commonwealth.
  • 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_69d87f26864c819088365ca381a003c2 completed April 10, 2026, 4:40 a.m.
NER Named-entity recognition batch_69e2da08fbc88190a31127d10ca633d6 completed April 18, 2026, 1:10 a.m.
NED1 Entity disambiguation (via context triple) batch_6a00261b31c08190908a72bff20871be completed May 10, 2026, 6:30 a.m.
Created at: April 10, 2026, 5:07 a.m.