A named entity recognition dataset for Turkish

Küçük, Dilek; Küçük, Doğan; Arıcı, Nursal

doi:10.1109/siu.2016.7495744

Cited by 7 publications

(1 citation statement)

References 6 publications

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“…O ¨zkaya and Diri [12] used conditional random fields (CRFs) to realise the recognition of three different entity names namely person, organisation and location by deducting some rules on unofficial Turkish e-mails. Ku ¨c xu ¨k et al [13] presented a dataset of news texts marked with entity names for Turkish. Gu ¨ngo ¨r et al [14] devised a method that uses recursive neural networks for the Turkish NER task.…”

Section: Introductionmentioning

confidence: 99%

Searchable Turkish OCRed historical newspaper collection 1928–1942

Menhour

Şahin

Sarıkaya

et al. 2021

Journal of Information Science

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The newspaper emerged as a distinct cultural form in early 17th-century Europe. It is bound up with the early modern period of history. Historical newspapers are of utmost importance to nations and its people, and researchers from different disciplines rely on these papers to improve our understanding of the past. In pursuit of satisfying this need, Istanbul University Head Office of Library and Documentation provides access to a big database of scanned historical newspapers. To take it another step further and make the documents more accessible, we need to run optical character recognition (OCR) and named entity recognition (NER) tasks on the whole database and index the results to allow for full-text search mechanism. We design and implement a system encompassing the whole pipeline starting from scrapping the dataset from the original website to providing a graphical user interface to run search queries, and it manages to do that successfully. Proposed system provides to search people, culture and security-related keywords and to visualise them.

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Section: Introductionmentioning

confidence: 99%