[PDF] Top 20 Low resource named entity recognition via multi source projection: Not quite there yet?

... annotation projection from multiple sources does work for cross-lingual ...true low- resource languages, and we have to do with more limited resources such as ...standalone projection yields ... See full document

... Named Entity Recognition is a well estab- lished information extraction task with many state of the art systems existing for a va- riety of ...and low data transfer settings with no task ... See full document

... (an entity responsible for providing the annotation content), Subject (what the annotation is about), Resources (the resources that have been used in the annotation session), Language and Date (a date associated ... See full document

... other source lan- guages, such as Catalan ...the low-resource case, the log-linear CRF outperforms the neural ...the low-resource case (when we have little target language data), as we ... See full document

... multiple source languages by projecting their annotations via the statistical word alignments traditionally used in Machine ...the Named Entity Recognition (NER) task as a use case, ... See full document

... The extraction of named entities in free text has been one of the most important tasks in NLP and information extraction (IE). As a result, this track of research has matured over the last two decades, especially ... See full document

... We have presented work on adapting a multilingual NER system to the Arabic language. The otherwise mostly language-independent rules had to be adapted to Arabic, mostly because the lack of case information makes it ... See full document

... The state-of-the-art NER systems are super- vised machine learning models (Nadeau and Sekine, 2007), including maximum entropy Markov models (MEMMs) (McCallum et al., 2000), conditional random fields (CRFs) (Lafferty et ... See full document

... Named Entity Recognition (NER) mod- els for language L are typically trained using annotated data in that ...other, source, language (or multiple source ...on low- ... See full document

... Adversarial Learning Adversarial learn- ing originates from Generative Adversarial Nets (GAN) (Goodfellow et al., 2014), which shows impressing results in computer vision. Recently, many papers have tried to apply ... See full document

... This paper describes a multi-task neural net- work that aims at generalizing the underneath rules of emerging NEs in user-generated text. In addition to the main category classification task, we employ an ... See full document

... As for Social Media (SM) domain, the raw sentences are from the messages on Sina-Weibo (weibo.com). We apply the similar strategy as HCI to annotate the sentences. Three types of entities are defined : Person-name (PER), ... See full document

... working on more language releases (Slovak, Pol- ish and Arabic). We are also aware that the cre- ation of the dictionary relies on the existence of a resource annotated with forms, lemmas and tags, which may not ... See full document

... e.g., named entity recognition. Segment-based known as entity recognition methods achieve much better correctness than the word- based alternative ... See full document

... The performance of a text classification model is heavily dependent upon the type of words used in the corpus and type of features created for classification.Text ba[r] ... See full document

... We chose this scheme despite previous research on NER for Norwegian has chosen a more granular approach (e.g. Haaland (2008); Jónsdóttir (2003); Nøklestad (2009)) This meant that we are to be able to more easily compare ... See full document

... Many named entities contain other named entities inside ...of named entity recognition has al- most entirely ignored nested named en- tity recognition, but due to ... See full document

... To investigate the role of gazetteers in NER, Mikheev et al. (1999) combine grammar rules with maximum entropy models and vary the gazetteer size. Experimental results show that (1) the F- scores for NE classes like ... See full document

... humans, low dose buprenorphine use exhibited antidepressant effects within the first 3 weeks of treatment in adults with treatment-resistant depression 46 ... See full document

... We proposed doing joint learning of NER and EL, in order to improve their performance. Results show that our model achieves results competitive with the state-of-the-art. Moreover, we verified that the models trained ... See full document