We optionally include additional variables that perform word sense disambiguation for each predicate.
To compare to prior work (i.e., submissions to the CoNLL-2009 Shared Task), we also consider the joint task of semantic role labeling and predicate sense disambiguation .
Table 4(b) contrasts our high-resource results for the task of SRL and sense disambiguation with the top systems in the CoNLL-2009 Shared Task, giving further insight into the performance of the simple information gain feature selection technique.
Table 5: F1 for SRL approaches (without sense disambiguation ) in matched and mismatched trairfltest settings for CoNLL 2005 span and 2008 head supervision.
Our method is significantly different from preVious word sense disambiguation reformulated for machine translation in that the latter neglects word senses in nature.
Results show that the proposed model substantially outperforms not only the baseline but also the preVious reformulated word sense disambiguation .
5.5 Comparison to Word Sense Disambiguation
Therefore a natural assumption is that word sense disambiguation (WSD) may contribute to statistical machine translation (SMT) by providing appropriate word senses for target translation selection with context features (Carpuat and Wu, 2005).
|WSI-Based Broad-Coverage Sense Tagger|
The biggest difference from word sense disambiguation lies in that WSI does not rely on a predefined sense inventory.
As applications of the resulting semantic frames and verb classes, we plan to integrate them into syntactic parsing, semantic role labeling and verb sense disambiguation .
Such verb classes have been used in many NLP applications that need to consider semantics in particular, such as word sense disambiguation (Dang, 2004), semantic parsing (Swier and Stevenson, 2005; Shi and Mihalcea, 2005) and discourse parsing (Subba and Di Eugenio, 2009).
For each predicate-argument structure of a verb, we couple the verb and an argument to make a unit for sense disambiguation .
They conducted several evaluations including predominant class induction and token-level verb sense disambiguation , but did not evaluate multiple classes output by their models.
Our approach can be applied for lexicography, as well as for applications like word sense disambiguation or semantic search.
Two of the fundamental components of a natural language communication are word sense discovery (Jones, 1986) and word sense disambiguation (Ide and Veronis, 1998).
Word sense disambiguation as well as word sense discovery have both remained key areas of research right from the very early initiatives in natural language processing research.
Ide and Vero-nis (1998) present a very concise survey of the history of ideas used in word sense disambiguation ; for a recent survey of the state-of-the-art one can refer to (Navigli, 2009).
The edges obtained from unambiguous entries are essentially sense disambiguated on both sides whereas those obtained from ambiguous terms are a result of our similarity-based disambiguation.
Owing to its ability to bring together features like multilin-guality and increasing coverage, over the past few years resource alignment has proven beneficial to a wide spectrum of tasks, such as Semantic Parsing (Shi and Mihalcea, 2005), Semantic Role Labeling (Palmer et al., 2010), and Word Sense Disambiguation (Navigli and Ponzetto, 2012).
PPR has been previously used in a wide variety of tasks such as definition similarity-based resource alignment (Niemann and Gurevych, 2011), textual semantic similarity (Hughes and Ramage, 2007; Pilehvar et al., 2013), Word Sense Disambiguation (Agirre and Soroa, 2009; Faralli and Navigli, 2012) and semantic text categorization (Navigli et al., 2011).