Triple

T5548873
Position Surface form Disambiguated ID Type / Status
Subject Narrow Bantu E145475 entity
Predicate includes P1393 FINISHED
Object Chichewa language E55892 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: Chichewa language | Statement: [Narrow Bantu, includes, Chichewa language]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Chichewa language
Context triple: [Narrow Bantu, includes, Chichewa language]
  • A. Chichewa chosen
    Chichewa is a major Bantu language spoken primarily in Malawi and neighboring countries, serving as a national and widely used lingua franca in the region.
  • B. Tumbuka
    Tumbuka is a Bantu language spoken primarily in northern Malawi and parts of Zambia and Tanzania.
  • C. Malaweg language
    The Malaweg language is an Austronesian language spoken primarily in the northern Philippines, particularly in parts of Cagayan province, by the Malaweg ethnic group.
  • D. Kimbundu
    Kimbundu is a major Bantu language spoken primarily in northwestern Angola, especially around the capital Luanda, by the Ambundu people.
  • E. Temne language
    Temne is a major Niger-Congo language spoken primarily by the Temne people of Sierra Leone, where it has significantly shaped the country’s linguistic and cultural landscape.
  • 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_69c008fb879c81909f5bfa56fadc1d46 completed March 22, 2026, 3:21 p.m.
NER Named-entity recognition batch_69c01fe143ec8190bb67d2530c92a419 completed March 22, 2026, 4:59 p.m.
NED1 Entity disambiguation (via context triple) batch_69c0282dd7408190ad762fca9ff5e04b completed March 22, 2026, 5:34 p.m.
Created at: March 22, 2026, 3:35 p.m.