
Named entity recognition (NER) is the problem of locating and categorizing important nouns and proper nouns in a text. In this chapter, we review the general state of research on entity recognition, relevant challenges and the current state of the art works on named entity recognition on Semitic languages. Specifically, we look into two case studies for Arabic and Hebrew. We also review Semitic NLP tasks which overlap with the named entity recognition. We close with an overview of the available resources for Semitic named entity recognition and some the open.research questions.
| selected citations These citations are derived from selected sources. This is an alternative to the "Influence" indicator, which also reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically). | 89 | |
| popularity This indicator reflects the "current" impact/attention (the "hype") of an article in the research community at large, based on the underlying citation network. | Top 1% | |
| influence This indicator reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically). | Top 10% | |
| impulse This indicator reflects the initial momentum of an article directly after its publication, based on the underlying citation network. | Average |
