A computer-implemented method of generating discrete structured data items for an electronic record comprising: receiving an original text that is a representation of a narration of a patient encounter provided by a clinician; reformatting the original text to produce a formatted text, the step of reformatting using a processor which applies a statistical model to predict sentence and/ or section boundaries in the original text, the model trained on a corpus of documents with correct punctuation and/ or section headings; extracting one or more clinical facts from the formatted text, wherein each fact of the one or more clinical facts is extracted from a corresponding portion of the formatted text, wherein the corresponding portion of the formatted text is a formatted version of a corresponding portion of the original text, wherein the step of extracting comprises using a clinical language understanding engine to parse the formatted text to identify clinical terms in a lexicon of a clinical language, identify concepts linked to the clinical terms in a formal ontology and extract facts based on the linguistic knowledge in the formal ontology; maintaining a linkage between each fact and the corresponding portion of the original text; displaying the one or more clinical fact in a fact panel on a graphical user interface: responsive to selection by a user of one of the facts displayed in the fact panel, displaying an indication of the corresponding portion of the original text from which the selected fact was extracted to a user on a graphical user interface, whereby the user can review extracted facts with reference to the original text and make one or more change to one or more of the extracted facts to provide a set of clinical facts for the patient encounter; storing the set of clinical facts corresponding to the patient encounter, comprising extracted facts and any changed facts provided by the user, as discrete structured data items in an electronic medical record. receiving an original text that is a representation of a narration of a patient encounter provided by a clinician; reformatting the original text to produce a formatted text, the step of reformatting using a processor which applies a statistical model to predict sentence and/ or section boundaries in the original text, the model trained on a corpus of documents with correct punctuation and/ or section headings; extracting one or more clinical facts from the formatted text, wherein each fact of the one or more clinical facts is extracted from a corresponding portion of the formatted text, wherein the corresponding portion of the formatted text is a formatted version of a corresponding portion of the original text, wherein the step of extracting comprises using a clinical language understanding engine to parse the formatted text to identify clinical terms in a lexicon of a clinical language, identify concepts linked to the clinical terms in a formal ontology and extract facts based on the linguistic knowledge in the formal ontology; maintaining a linkage between each fact and the corresponding portion of the original text; displaying the one or more clinical fact in a fact panel on a graphical user interface: responsive to selection by a user of one of the facts displayed in the fact panel, displaying an indication of the corresponding portion of the original text from which the selected fact was extracted to a user on a graphical user interface, whereby the user can review extracted facts with reference to the original text and make one or more change to one or more of the extracted facts to provide a set of clinical facts for the patient encounter; storing the set of clinical facts corresponding to the patient encounter, comprising extracted facts and any changed facts provided by the user, as discrete structured data items in an electronic medical record. responsive to selection by a user of one of the facts displayed in the fact panel, displaying an indication of the corresponding portion of the original text from which the selected fact was extracted to a user on a graphical user interface, whereby the user can review extracted facts with reference to the original text and make one or more change to one or more of the extracted facts to provide a set of clinical facts for the patient encounter; storing the set of clinical facts corresponding to the patient encounter, comprising extracted facts and any changed facts provided by the user, as discrete structured data items in an electronic medical record.