This paper describes an information extraction system designed for obtaining CV-style structured information about publicly mentioned persons, organizations and their relations by analyzing newswire archives in the Latvian language. The described text analysis pipeline consists of morphosyntactic analysis, NER and coreference resolution, and a semantic role labeling system based on FrameNet principles. We also implement an entity linking process, matching the entity mentions in each document to an entity knowledge base that is initially seeded with authoritative information on relevant people and organizations. The accuracy of automated frame extraction varies depending on specifics of each frame type, but the average accuracy currently is 53% F-score for frame target identification, and 61% for frame element role classification. The currently targeted volume of text is the total archives of Latvian newspapers, magazines and news portals, consisting of about 3.5 million articles.
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