[PDF] Top 20 Supervised All Words Lexical Substitution using Delexicalized Features
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Supervised All Words Lexical Substitution using Delexicalized Features
... a supervised lexical substitu- tion system that does not use separate clas- sifiers per word and is therefore applicable to any word in the ...word-specific substitution patterns, a global model for ... See full document
11
BERT based Lexical Substitution
... substitute words; and supervised learning approaches (Biemann, 2013; Szarvas et ...uses delexicalized features to rank substitute can- ...for substitution, they are not perfect and they ... See full document
6
Do Supervised Distributional Methods Really Learn Lexical Inference Relations?
... contextual features of single words are not learning lexical inference relations because contextual features might lack the necessary infor- mation to deduce how one word relates to ... See full document
7
Combining Lexical and Syntactic Features for Supervised Word Sense Disambiguation
... binary features representing the possible values of a given sequence of part of speech tags outperforms one based on individ- ual ...obtained using the parts of speech of words following the target ... See full document
8
A Vector Space for Distributional Semantics for Entailment
... Distributional semantics creates vector- space representations that capture many forms of semantic similarity, but their re- lation to semantic entailment has been less clear. We propose a vector-space model which ... See full document
11
Simplification Using Paraphrases and Context Based Lexical Substitution
... complex words or phrases that need to be sim- plified, and recommending simpler meaning- preserving substitutes that can be more eas- ily ...both lexical and contextual features, and a simpli- ... See full document
11
Learning to Rank Lexical Substitutions
... characterized using non-lexical features from heterogeneous evidence such as lexical-semantic resources and distributional similarity, n-gram counts and shallow syntactic fea- tures computed ... See full document
7
Lexical Substitution for the Medical Domain
... of words their thesauri en- tries share, considering the top n words in each entry with n = 1, 5, 20, 50, 100, ...4.1). Using this information, we compute if the words in the sentences also ... See full document
5
Cross lingual transfer parser from Hindi to Bengali using delexicalization and chunking
... of words (Mikolov et ...lingual lexical information and can be augmented with delexicalized ...combined all sentences from both languages to induce real-valued distributed representation of ... See full document
10
Language Transfer Learning for Supervised Lexical Substitution
... across all three ...full lexical substitution task, whereas Table 4 shows results for the ranking-only ...for all languages (~ 2000 ...throughout all datasets for the open candidate ... See full document
12
Metaheuristic Approaches to Lexical Substitution and Simplification
... The more challenging baseline performance comes from the best-performing participating sys- tems at GermEval 2015, which represent the state of the art in German-language lexical substitution. One of these ... See full document
11
Unsupervised Cross Lingual Lexical Substitution
... Cross-Lingual Lexical Substitution (CLLS) is the task that aims at providing for a target word in context, several alternative substitute words in another ...of words by cluster- ing their ... See full document
11
Probabilistic models of similarity in syntactic context
... pairs using 15 verbs, balanced across high and low expected ...data using a scale of 1–7; Mitchell and Lapata cal- culate average interannotator correlation to be ... See full document
11
Personalized Substitution Ranking for Lexical Simplification
... other lexical sub- stitution corpora such as the 2007 English Lexi- cal Substitution shared task (McCarthy and Nav- igli, 2009) and CoInCo (Kremer et ... See full document
10
Classifying easy to read texts without parsing
... RO 49.7 (0.9) 49.8 89.3 48.8 10.1 PM 49.7 (1.3) 49.8 95.0 54.9 4.4 Table 2: Performance of the POS-tag ratio param- eters ordered by performance. The various mod- els are tags used in the SUC corpus (Ejerhed et al., ... See full document
9
Mention Detection Crossing the Language Barrier
... The approach proposed in this article requires a mention detection system build in a resource-rich language, and a translation from the source lan- guage to the resource-rich language, together with word alignment. This ... See full document
10
Lexical Substitution Dataset for German
... of all possible ...for all words was ...English substitution task where the nouns also had the highest agreement score, followed by the verbs and by the ... See full document
6
Location Name Disambiguation Exploiting Spatial Proximity and Temporal Consistency
... We create an SVM classifier for each LEX to solve location name disambiguation with the features de- scribed in Section 4. This classifier identifies the LE for an ambiguous LEX included in a tweet. Since location ... See full document
9
Learning Word Representations from Scarce and Noisy Data with Embedding Subspaces
... or features prior to supervised ...retrained using the available labeled ...of supervised data is available, this can lead to severe ...the words will actu- ally be present in the ... See full document
11
Authorial Studies using Ranked Lexical Features
... The purpose of this article is to propose a tool for measuring distances between different styles of one or more authors. The main study is focused on measuring and visualizing distances in a space induced by ranked ... See full document
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