Triple

T6120416
Position Surface form Disambiguated ID Type / Status
Subject Yao E136467 entity
Predicate hasDialects P4251 FINISHED
Object Malawi Yao
Malawi Yao is a regional variety of the Yao language spoken primarily in Malawi, distinguished by its own phonological and lexical features.
 E570025 NE FINISHED

How this triple was built (4 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 Yao | Statement: [Yao, hasDialects, Malawi Yao]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07 
Target entity: Malawi Yao
Context triple: [Yao, hasDialects, Malawi Yao]
  • A. 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.
  • B. Silozi
    Silozi is a Bantu language spoken primarily by the Lozi people of western Zambia and surrounding regions.
  • C. Malaweg
    Malaweg is a Philippine language of northern Luzon, considered a variety or closely related member of the Ibanag language group.
  • D. Luba
    Luba is a coastal town and important port on the southern part of Bioko Island in Equatorial Guinea.
  • E. Luba
    The Luba are a major Bantu-speaking ethnic group of Central Africa, historically known for the powerful Luba Kingdom centered in what is now the Democratic Republic of the Congo.
  • F. None of above. chosen
  • G. Unsure - the case is ambiguous/there is not enough information to decide.
NEDg Description generation gpt-5.1
Instruction
Generate a one-sentence description of the target entity. 
You are given a context triple in the form (subject, predicate, object), where the object is the target entity. 
# Instructions
Use the triple to infer relevant information about the entity. Describe the entity based on what is most defining, well-known. 
Avoid repeating the information from the triple, unless really essential.
# Response Format
Return only the sentence: "Description: [one-sentence description of the target entity]"
Input
Entity: Malawi Yao
Triple: [Yao, hasDialects, Malawi Yao]
Generated description
Malawi Yao is a regional variety of the Yao language spoken primarily in Malawi, distinguished by its own phonological and lexical features.
NED2 Entity disambiguation (via description) gpt-5-mini-2025-08-07 
Target entity: Malawi Yao
Target entity description: Malawi Yao is a regional variety of the Yao language spoken primarily in Malawi, distinguished by its own phonological and lexical features.
  • A. 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.
  • B. Silozi
    Silozi is a Bantu language spoken primarily by the Lozi people of western Zambia and surrounding regions.
  • C. Malaweg
    Malaweg is a Philippine language of northern Luzon, considered a variety or closely related member of the Ibanag language group.
  • D. Luba
    Luba is a coastal town and important port on the southern part of Bioko Island in Equatorial Guinea.
  • E. Luba
    The Luba are a major Bantu-speaking ethnic group of Central Africa, historically known for the powerful Luba Kingdom centered in what is now the Democratic Republic of the Congo.
  • F. None of above. chosen

Provenance (5 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_69c0089f851c81909e5e189a617dcff6 completed March 22, 2026, 3:19 p.m.
NER Named-entity recognition batch_69c05bef8dc08190b917ad7209188c62 completed March 22, 2026, 9:15 p.m.
NED1 Entity disambiguation (via context triple) batch_69c1257153748190947cd80589620f12 completed March 23, 2026, 11:35 a.m.
NEDg Description generation batch_69c129464108819086b1a3991ef4c9e1 completed March 23, 2026, 11:51 a.m.
NED2 Entity disambiguation (via description) batch_69c129d7cd348190963e1a266d5e88ae completed March 23, 2026, 11:53 a.m.
Created at: March 22, 2026, 4:14 p.m.