Fix some links and add code link to Strubell 2017

named_entity_recognition.md

@@ -48,14 +48,14 @@ Links: [WNUT 2017 Emerging Entity task page](https://noisy-text.github.io/2017/e
 
 ### Ontonotes v5 (English)
 
-The [Ontonotes corpus v5]() is a richly annotated corpus with several layers of annotation, including named entities, coreference, part of speech, and constituency parse trees. These annotations are over a large number of tokens, a broad cross-section of domains, and 3 languages (English, Arabic, and Chinese). The common datasplit used in NER is defined in [Pradhan et al 2013](https://www.semanticscholar.org/paper/Towards-Robust-Linguistic-Analysis-using-OntoNotes-Pradhan-Moschitti/a94e4fe6f475e047be5dcc9077f445e496240852) and can be found [here](http://cemantix.org/data/ontonotes.html).
+The [Ontonotes corpus v5](https://www.semanticscholar.org/paper/Towards-Robust-Linguistic-Analysis-using-OntoNotes-Pradhan-Moschitti/a94e4fe6f475e047be5dcc9077f445e496240852) is a richly annotated corpus with several layers of annotation, including named entities, coreference, part of speech, and constituency parse trees. These annotations are over a large number of tokens, a broad cross-section of domains, and 3 languages (English, Arabic, and Chinese). The common datasplit used in NER is defined in [Pradhan et al 2013](https://www.semanticscholar.org/paper/Towards-Robust-Linguistic-Analysis-using-OntoNotes-Pradhan-Moschitti/a94e4fe6f475e047be5dcc9077f445e496240852) and can be found [here](http://cemantix.org/data/ontonotes.html).
 
 | Model           | F1  |  Paper / Source | Code |
 | ------------- | :-----:| --- | --- |
-| BiLSTM-CRF (Strubell et al, 2017) | 86.99 | [Fast and Accurate Entity Recognition with Iterated Dilated Convolutions](https://arxiv.org/pdf/1702.02098.pdf)  |  |
-| Iterated Dilated CNN (Strubell et al, 2017) | 86.84 | [Fast and Accurate Entity Recognition with Iterated Dilated Convolutions](https://arxiv.org/pdf/1702.02098.pdf)  |  |
+| BiLSTM-CRF (Strubell et al, 2017) | 86.99 | [Fast and Accurate Entity Recognition with Iterated Dilated Convolutions](https://arxiv.org/pdf/1702.02098.pdf)  | [Code](https://github.com/iesl/dilated-cnn-ner) |
+| Iterated Dilated CNN (Strubell et al, 2017) | 86.84 | [Fast and Accurate Entity Recognition with Iterated Dilated Convolutions](https://arxiv.org/pdf/1702.02098.pdf)  | [Code](https://github.com/iesl/dilated-cnn-ner) |
 | Joint Model (Durrett and Klein 2014) | 84.04 | [A Joint Model for Entity Analysis: Coreference, Typing, and Linking](https://pdfs.semanticscholar.org/2eaf/f2205c56378e715d8d12c521d045c0756a76.pdf) |
-| Averaged Perceptron (Ratinov and Roth 2009) | 83.45 | [Design Challenges and Misconceptions in Named Entity Recognition](https://www.semanticscholar.org/paper/Design-Challenges-and-Misconceptions-in-Named-Ratinov-Roth/27496a2ee337db705e7c611dea1fd8e6f41437c2) (These scores reported in [Durrett and Klein 2014](https://pdfs.semanticscholar.org/2eaf/f2205c56378e715d8d12c521d045c0756a76.pdf) ||
+| Averaged Perceptron (Ratinov and Roth 2009) | 83.45 | [Design Challenges and Misconceptions in Named Entity Recognition](https://www.semanticscholar.org/paper/Design-Challenges-and-Misconceptions-in-Named-Ratinov-Roth/27496a2ee337db705e7c611dea1fd8e6f41437c2) (These scores reported in ([Durrett and Klein 2014](https://pdfs.semanticscholar.org/2eaf/f2205c56378e715d8d12c521d045c0756a76.pdf))) ||