Triple

T5825680
Position Surface form Disambiguated ID Type / Status
Subject Mfecane E129216 entity
Predicate hasKeyGroup P46138 FINISHED
Object Swazi E16080 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: Swazi | Statement: [Mfecane, hasKeyGroup, Swazi]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Swazi
Context triple: [Mfecane, hasKeyGroup, Swazi]
  • A. Eswatini chosen
    Eswatini is a small landlocked monarchy in Southern Africa known for its blend of traditional Swazi culture and modern institutions.
  • B. Lesotho
    Lesotho is a small, landlocked constitutional monarchy in Southern Africa, entirely surrounded by South Africa and known for its mountainous terrain and high-altitude settlements.
  • C. Kwaluseni
    Kwaluseni is a town in Eswatini known primarily as the main campus site of the University of Eswatini.
  • D. Siphofaneni, Eswatini
    Siphofaneni is a rural town in central Eswatini known as an agricultural and transport hub situated near the Great Usutu River.
  • E. Motswana
    A Motswana is an individual belonging to the Tswana ethnic group, primarily associated with the country of Botswana and neighboring regions of Southern Africa.
  • 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_69c00849d55481908b4f9f5543e0bf6d completed March 22, 2026, 3:18 p.m.
NER Named-entity recognition batch_69c0341a85988190be988f1c0722da66 completed March 22, 2026, 6:25 p.m.
NED1 Entity disambiguation (via context triple) batch_69c0a188e5c08190abbc283eff193761 completed March 23, 2026, 2:12 a.m.
Created at: March 22, 2026, 3:53 p.m.