Белгілеу дәлдігі

Bootstrap methods (unsupervised classification) that generate word classes without requiring pretagging have had notable success in the last few years. The methods described here strengthen these approaches and produce excellent …...

We present a statistical model of Japanese unknown words consisting of a set of length and spelling models classified by the character types that con- stitute a word. The point …...

In order to achieve fast, high quality Part-of-speech (pos) tagging, algorithms should achieve high accuracy and require less manually proofreading. This study aimed to achieve these goals by defining a …...

Model minimization has been shown to work well for the task of unsupervised part-of-speech tagging with a dictionary. In (Ravi and Knight, 2009), the authors in- voke an integer programming …...

AbstractIn this paper, we describe our generic approach for transferring part-of-speech annotations from a resourced language towards an etymologically closely related non-resourced language, without using any bilingual (i.e., parallel) data. …...

AbstractIn this paper, we describe the correction of PoS tags in a new Icelandic corpus, MIM-GOLD, consisting of about 1 million tokens sampled from the Tagged Icelandic Corpus, MÍM, released …...

AbstractThe paper presents a design schema and details of a new Urdu POS tagset. This tagset is designed due to challenges encountered in working with existing tagsets for Urdu. It …...

We present a simple, yet effective approach to adapt part-of-speech (POS) taggers to new domains. Our approach only requires a dic- tionary and large amounts of unlabeled tar- get data. …...

Part-of-speech (POS) taggers trained on newswire perform much worse on domains such as subtitles, lyrics, or tweets. In addition, these domains are also heterogeneous, e.g., with respect to registers and …...

As more historical texts are digitized, there is interest in applying natural language pro- cessing tools to these archives. However, the performance of these tools is often unsatisfac- tory, due …...

AbstractThe performance of a Part-of-speech (POS) tagger is highly dependent on the domain of the processed text, and for many domains there is no or only very little training data …...

Named Entity Recognition (NER) is an essential task in Natural Language Processing. Memory Enhanced CRF (MECRF) integrates external memory to extend Conditional Random Field (CRF) to capture long-range dependencies with …...

Named Entity Recognition (NER) is an essential task in Natural Language Processing. Memory Enhanced CRF (MECRF) integrates external memory to extend Conditional Random Field (CRF) to capture long-range dependencies with …...