Name
Title | ||
|---|---|---|
A Unified Framework To Identify And Extract Uncertainty Cues, Holders, And Scopes In One Fell-Swoop |
Abstract | ||
|---|---|---|
We present a unified framework based on supervised sequence labelling methods to identify and extract uncertainty cues, holders, and scopes in one-fell swoop with an application on Arabic tweets. The underlying technology employs Support Vector Machines with a rich set of morphological, syntactic, lexical, semantic, pragmatic, dialectal, and genre-specific features, and yields an average F-1 score of 0.759. |
Year | DOI | Venue |
|---|---|---|
2015 | 10.1007/978-3-319-18111-0_24 | COMPUTATIONAL LINGUISTICS AND INTELLIGENT TEXT PROCESSING (CICLING 2015), PT I |
Keywords | DocType | Volume |
Uncertainty Automatic Analysis, Supervised Sequence Labeling, Unified Frameworks, Morphologically-Rich Languages, Twitter | Conference | 9041 |
ISSN | Citations | PageRank |
0302-9743 | 0 | 0.34 |
References | Authors | |
41 | 3 | |
Name | Order | Citations | PageRank |
|---|---|---|---|
| Rania Al-Sabbagh | 1 | 42 | 4.22 |
| R. Girju | 2 | 14 | 1.53 |
| Jana Diesner | 3 | 22 | 5.86 |