Manzini (formerly Bremersdorp) is a large city in Eswatini, which is also the city of Eswatini's Manzini Region. The city is the country's second largest urban center behind the capital Mbabane, with a population of 110,000 (2008). It is known as "The Hub" of Eswatini and lies on the MR3 road. Eswatini's primary industrial site at Matsapha lies near the town's western border.
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{{Infobox settlement | name = Manzini | settlement_type = City | image_skyline = SZ-manzini-zufahrt.jpg | image_alt = Road of Manzini | image_caption = | etymology = | nickname = | pushpin_map = Eswatini | mapsize = 300px | map_alt = | map_caption = Location of Manzini in Eswatini | coordinates = | subdivision_type = Country | subdivision_name = | subdivision_type1 = Region | subdivision_name1 = Manzini Region | subdivision_type2 = | subdivision_name2 = | leader_title = Mayor | leader_name = Wesley Dlamini | population_as_of = 2008 | population_footnotes = <!-- for references: use
==Geography== Residential areas radiate outward from the Central Business District. At the western terminus of the city on the highway to Mbabane is KaKhoza Township, a poor neighborhood with the appearance of an informal settlement. North of downtown beyond the Mavuso International Trade Fair (opened 2004) along a bypass road (opened 1994, rebuilt 2004 for the opening of the Mavuso Trade Fair) is Helemesi Estates. Here middle-class dwellings were erected in the early 1990s on the former farm of Sydney Williams, the long-serving Resident Commissioner during British rule. Helemesi is the SiSwati corruption of the name Williams. The housing development is surrounded by Fairview Township, developed in 1964 during the twilight of colonial rule as Eswatini's first integrated residential neighborhood. The 19th-century law, reaffirmed by ordinances in the 1920s, forbade Swazis from residing or owning businesses in Bremserdorp. Until the 1960s Swazi business proprietors used Europeans as fronts in order to operate "Native Eating Houses" and other establishments.
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Discovered by embedding cosine similarity (sentence-transformers MiniLM, 384-dim).