Twitter Universal Dependency Parsing for African-American and Mainstream American English (P18-1)
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| Challenge: | We analyze the performance disparities between AAE and Mainstream American English (MAE) because of Twitter-specific conventions and dialectal language. |
| Approach: | They develop a dataset of 500 tweets, 250 of which are in AAE, within the Universal Dependencies 2.0 framework and annotate it. |
| Outcome: | The proposed model improves performance for AAE tweets with no or very little in-domain labeled data and assesses its lexical and syntactic features. |
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