Browse transcripts » Amsterdam City Archives
Transcription
Hooft: G. 525 Hakke. G. H 7 V.o — 11 Vo Hartemink. P. 170o Houtkamp. Hofman. BB. 18 Vo Hutter H 29 Hutten.B. 35. Hontappel. G. I. 41 Heigmans. M: P. 52 Vo Haan J: de. 54. 67 Vo Huygens. A: . . . Houthugden. G. M. .97. Hacker I: A: 103 Hart. 114 Hummer. H. 119 Houthuysen. J. 7 120. Henke. I: F: 12017 Henkelman. I. 126 Vo Huesen. W: A: 127 Ilaverkamp. S. 133. Hlam. J: 5 Huysman. A: 154. Hessing. H: 164. 167. Holswaart. 17487 Hinse. D: S Hoorn J van 181. 18710 Hassallar. F. Herfst. A: B: 188. Hofland. P. 192. 192 Vo Heer I: M. Jurgens. H:: ..90 Jans . ad 1 Jay. H: Le.. 5 28 Vo Joolen. van . . 44. Jagt: P. van der 46 62 sking. P. 77. Idem. K: Jonker W.J. 117 Vo 130 Vo Judik. A. 10 151O. Idees. R. 1 156. Jagtman. . 186 Vo Impelen. A: van 10 198 . Jongh. I: A: de
Source citation
Amsterdam City Archives, archive number 5009, Archief van de Burgerlijke stand, inventory number 1092, Huwelijken en echtscheidingen, Akten, Registers van huwelijksakten en echtscheidingsakten, 1828, deel 2
Scan + Transcription
Click on the image to enlarge it and see the transcription next to it
Artificial Intelligence (AI)
The transcription was made by computer via automatic handwriting recognition.
The summary is created by the computer based on a language model.
Both artificial intelligence tasks are not perfect, but often more than sufficient so that the historical document becomes understandable.
The summary is created by the computer based on a language model.
Both artificial intelligence tasks are not perfect, but often more than sufficient so that the historical document becomes understandable.