Triple
T15871621
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Government of Lesotho |
E384841
|
entity |
| Predicate | usesCurrency |
P188
|
FINISHED |
| Object | Lesotho loti |
E78540
|
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: Lesotho loti | Statement: [Government of Lesotho, usesCurrency, Lesotho loti]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Lesotho loti Context triple: [Government of Lesotho, usesCurrency, Lesotho loti]
-
A.
Lesotho loti
chosen
The Lesotho loti is the official monetary unit of the Kingdom of Lesotho, typically used alongside the South African rand.
-
B.
Loto
Loto is a small village on Pukapuka Atoll in the Cook Islands, known for its traditional Polynesian community and remote Pacific island setting.
-
C.
Mabalako
Mabalako is a health zone in North Kivu Province in the eastern Democratic Republic of the Congo, known for being heavily affected by Ebola outbreaks.
-
D.
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.
-
E.
Kwaluseni
Kwaluseni is a town in Eswatini known primarily as the main campus site of the University of Eswatini.
- 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_69d86da4e86481909f1325fdc971b5ec |
completed | April 10, 2026, 3:25 a.m. |
| NER | Named-entity recognition | batch_69e155fa1aac81908e4b86abedf295ca |
completed | April 16, 2026, 9:34 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69ffa94ca15c8190bdd5fe0a30b54b51 |
completed | May 9, 2026, 9:38 p.m. |
Created at: April 10, 2026, 4:50 a.m.