Triple

T16356390
Position Surface form Disambiguated ID Type / Status
Subject Swazi language E397190 entity
Predicate spokenIn P2266 FINISHED
Object Mozambique E13411 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: Mozambique | Statement: [Swazi language, spokenIn, Mozambique]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Mozambique
Context triple: [Swazi language, spokenIn, Mozambique]
  • A. Mozambique chosen
    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.
  • B. 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.
  • C. Malawi and Mozambique
    Malawi and Mozambique are neighboring countries in southeastern Africa that share a border traversed by the Shire River.
  • D. Malaweg
    Malaweg is a Philippine language of northern Luzon, considered a variety or closely related member of the Ibanag language group.
  • E. Tanzania
    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.
  • 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_69d87f2778dc8190aa95c7572db127e6 completed April 10, 2026, 4:40 a.m.
NER Named-entity recognition batch_69e2facf67e0819089a23ce6f5642fbe completed April 18, 2026, 3:30 a.m.
NED1 Entity disambiguation (via context triple) batch_6a002d99e8ec8190945812327283ba6c completed May 10, 2026, 7:02 a.m.
Created at: April 10, 2026, 5:07 a.m.