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Everything Is All It Takes: A Multipronged Strategy for Zero-Shot Cross-Lingual Information Extraction ...
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Fine-tuning Encoders for Improved Monolingual and Zero-shot Polylingual Neural Topic Modeling ...
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Cross-Lingual Transfer in Zero-Shot Cross-Language Entity Linking ...
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Fine-tuning Encoders for Improved Monolingual and Zero-shot Polylingual Neural Topic Modeling ...
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Do Explicit Alignments Robustly Improve Multilingual Encoders? ...
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Sources of Transfer in Multilingual Named Entity Recognition ...
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Cross-Lingual Transfer in Zero-Shot Cross-Language Entity Linking ...
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Learning unsupervised contextual representations for medical synonym discovery
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Improving Named Entity Recognition for Chinese Social Media with Word Segmentation Representation Learning ...
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Improved Relation Extraction with Feature-Rich Compositional Embedding Models ...
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Annotating named entities in Twitter data with crowdsourcing ...
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Reading the Markets: Forecasting Public Opinion of Political Candidates by News Analysis
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Reading the Markets: Forecasting Public Opinion of Political Candidates by News Analysis ...
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Further Results and Analysis of Icelandic Part of Speech Tagging
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In: Technical Reports (CIS) (2008)
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Abstract:
Data driven POS tagging has achieved good performance for English, but can still lag behind linguistic rule based taggers for morphologically complex languages, such as Icelandic. We extend a statistical tagger to handle fine grained tagsets and improve over the best Icelandic POS tagger. Additionally, we develop a case tagger for non-local case and gender decisions. An error analysis of our system suggests future directions. This paper presents further results and analysis to the original work (Dredze and Wallenberg, 2008).
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URL: https://repository.upenn.edu/cgi/viewcontent.cgi?article=1922&context=cis_reports https://repository.upenn.edu/cis_reports/878
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