Triple

T5614574
Position Surface form Disambiguated ID Type / Status
Subject Lomwe E147444 entity
Predicate hasDialect P4251 FINISHED
Object Malawi Lomwe E147444 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: Malawi Lomwe | Statement: [Lomwe, hasDialect, Malawi Lomwe]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Malawi Lomwe
Context triple: [Lomwe, hasDialect, Malawi Lomwe]
  • A. Lomwe chosen
    Lomwe is a Bantu language spoken primarily in Mozambique and Malawi by the Lomwe people.
  • B. Malaweg
    Malaweg is a Philippine language of northern Luzon, considered a variety or closely related member of the Ibanag language group.
  • C. 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.
  • D. Mzuzu
    Mzuzu is a major city in northern Malawi known as an important commercial and administrative center for the region.
  • E. Sioma, Zambia
    Sioma is a rural town in western Zambia known as a gateway to the scenic Ngonye Falls on the Zambezi River.
  • 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_69c00905d4588190bd967842bbcf2219 completed March 22, 2026, 3:21 p.m.
NER Named-entity recognition batch_69c02123fa9081909086c9cce3f3e907 completed March 22, 2026, 5:04 p.m.
NED1 Entity disambiguation (via context triple) batch_69c05a0ab9cc8190a01c5309e6cfc598 completed March 22, 2026, 9:07 p.m.
Created at: March 22, 2026, 3:39 p.m.