Triple

T19642039
Position Surface form Disambiguated ID Type / Status
Subject Anastasios Yannoulatos E471561 entity
Predicate countryOfWork P1527 FINISHED
Object Tanzania 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: Tanzania | Statement: [Anastasios Yannoulatos, countryOfWork, Tanzania]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Tanzania
Context triple: [Anastasios Yannoulatos, countryOfWork, 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 (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_69d8e511f28481909f4bc3ea9191e54a completed April 10, 2026, 11:54 a.m.
NER Named-entity recognition batch_69e64122d9f48190961c4b460256f9e7 completed April 20, 2026, 3:07 p.m.
Created at: April 10, 2026, 1:44 p.m.