Triple

T761564
Position Surface form Disambiguated ID Type / Status
Subject Eswatini E16080 entity
Predicate currency P245 FINISHED
Object Lilangeni
The lilangeni is the official monetary unit of Eswatini, subdivided into 100 cents and commonly used alongside the South African rand.
E103007 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: Lilangeni | Statement: [Eswatini, currency, Lilangeni]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Lilangeni
Context triple: [Eswatini, currency, Lilangeni]
  • A. Makhuwa
    Makhuwa is a major Bantu language spoken primarily in northern Mozambique by the Makhuwa people.
  • B. Kasulu
    Kasulu is a town in western Tanzania that serves as one of the main urban and commercial centers of the Kigoma Region.
  • C. Siyani
    Siyani is a given name most notably associated with Siyani Chambers, an American basketball player known for his collegiate career at Harvard University.
  • D. Thame
    Thame is a historic market town in Oxfordshire, England, known for its traditional architecture and vibrant local community.
  • E. Rolihlahla
    Rolihlahla is the Xhosa birth name of Nelson Mandela, meaning “troublemaker” and reflecting his cultural origins.
  • 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: Lilangeni
Triple: [Eswatini, currency, Lilangeni]
Generated description
The lilangeni is the official monetary unit of Eswatini, subdivided into 100 cents and commonly used alongside the South African rand.
NED2 Entity disambiguation (via description) gpt-5-mini-2025-08-07
Target entity: Lilangeni
Target entity description: The lilangeni is the official monetary unit of Eswatini, subdivided into 100 cents and commonly used alongside the South African rand.
  • A. Makhuwa
    Makhuwa is a major Bantu language spoken primarily in northern Mozambique by the Makhuwa people.
  • B. Kasulu
    Kasulu is a town in western Tanzania that serves as one of the main urban and commercial centers of the Kigoma Region.
  • C. Siyani
    Siyani is a given name most notably associated with Siyani Chambers, an American basketball player known for his collegiate career at Harvard University.
  • D. Thame
    Thame is a historic market town in Oxfordshire, England, known for its traditional architecture and vibrant local community.
  • E. Rolihlahla
    Rolihlahla is the Xhosa birth name of Nelson Mandela, meaning “troublemaker” and reflecting his cultural origins.
  • 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_69a493684ee48190bd43b7c78da4aec8 completed March 1, 2026, 7:28 p.m.
NER Named-entity recognition batch_69a4a682e7d081909c9cd7839a49fb0b completed March 1, 2026, 8:50 p.m.
NED1 Entity disambiguation (via context triple) batch_69a7b83948b48190af0349dd73ec3951 completed March 4, 2026, 4:42 a.m.
NEDg Description generation batch_69a7b99c19fc819090e0f9a042a8c12c completed March 4, 2026, 4:48 a.m.
NED2 Entity disambiguation (via description) batch_69a7ba44b79c8190b0ce8a430fe928e5 completed March 4, 2026, 4:51 a.m.
Created at: March 1, 2026, 7:37 p.m.