Index of papers in Proc. ACL 2014 that mention
  • synsets
Aliabadi, Purya
KurdNet: State-of-the-Art
0 Expand: in this model, the synsets are built in correspondence with the WordNet synsets and the semantic relations are directly imported.
KurdNet: State-of-the-Art
0 Merge: in this model, the synsets and relations are first built independently and then they are aligned with WordNet’s.
KurdNet: State-of-the-Art
synsets ) that play a major role in the wordnets.
synsets is mentioned in 23 sentences in this paper.
Topics mentioned in this paper:
Kang, Jun Seok and Feng, Song and Akoglu, Leman and Choi, Yejin
Evaluation 1: Agreement with Sentiment Lexicons
The construction of the connotation graph, denoted by GWORD+SENSE, which includes words and synsets , has been described in Section 2.
Introduction
1Hence a sense in WordNet is defined by synset (= synonym set), which is the set of words sharing the same sense.
Network of Words and Senses
As shown in Figure 1, it contains two types of nodes; (i) lemmas (i.e., words, 115K) and (ii) synsets (63K), and four types of edges; (t1) predicate-argument (179K), (t2) argument-argument (144K), (t3) argument-synset (126K), and (t4) synset-synset (3.4K) edges.
Network of Words and Senses
The argument-synset edges capture the synonymy between argument nodes through the corresponding synsets .
Network of Words and Senses
Finally, the synset-synset edges depict the antonym relations between synset pairs.
Pairwise Markov Random Fields and Loopy Belief Propagation
More formally, we denote the connotation graph GWORDJ'SEI‘ISE by G = (V, E), in which a total of n word and synset nodes V = {211, .
Pairwise Markov Random Fields and Loopy Belief Propagation
and synsets connected with typed edges, - prior knowledge (i.e., probabilities) of (some or all) nodes belonging to each class,
synsets is mentioned in 24 sentences in this paper.
Topics mentioned in this paper:
Lam, Khang Nhut and Al Tarouti, Feras and Kalita, Jugal
Abstract
As a first step to automatically construct full Wordnets, we propose approaches to generate Wordnet synsets for languages both resource-rich and resource-poor, using publicly available Wordnets, a machine translator and/or a single bilingual dictionary.
Abstract
Our algorithms translate synsets of existing Wordnets to a target language T, then apply a ranking method on the translation candidates to find best translations in T. Our approaches are applicable to any language which has at least one existing bilingual dictionary translating from English to it.
Introduction
One of our goals is to automatically generate high quality synsets , each of which is a set of cognitive synonyms, for Wordnets having the same structure as the PWN in several languages.
Introduction
In particular, given public Wordnets aligned to the PWN ( such as the FinnWordNet (FWN) (Linden, 2010) and the J apaneseWordNet (J WN) (Isahara et al., 2008) ) and the Microsoft Translator, we build Wordnet synsets for arb, asm, dis, ajz and vie.
Proposed approaches
In this section, we propose approaches to create Wordnet synsets for a target languages T using existing Wordnets and the MT and/or a single bilingual dictionary.
Proposed approaches
We take advantage of the fact that every synset in PWN has a unique oflset-POS, referring to the offset for a synset with a particular part-of—speech (POS) from the beginning of its data file.
Proposed approaches
Each synset may have one or more words, each of which may be in one or more synsets .
synsets is mentioned in 58 sentences in this paper.
Topics mentioned in this paper:
Mitra, Sunny and Mitra, Ritwik and Riedl, Martin and Biemann, Chris and Mukherjee, Animesh and Goyal, Pawan
Evaluation framework
The aligner constructs a WordNet dictionary for the purpose of synset alignment.
Evaluation framework
The CW cluster is then aligned to WordNet synsets by comparing the clusters with WordNet graph and the synset with the maximum alignment score is returned as the output.
Evaluation framework
In summary, the aligner tool takes as input the CW cluster and returns a WordNet synset id that corresponds to the cluster words.
Related work
A few approaches suggested by (Bond et al., 2009; Paakko' and Linden, 2012) attempt to augment WordNet synsets primarily using methods of annotation.
synsets is mentioned in 10 sentences in this paper.
Topics mentioned in this paper:
Pilehvar, Mohammad Taher and Navigli, Roberto
Experiments
To enable a comparison with the state of the art, we followed Matuschek and Gurevych (2013) and performed an alignment of WordNet synsets (WN) to three different collaboratively-constructed resources: Wikipedia
Experiments
As mentioned in Section 2.1.1, we build the WN graph by including all the synsets and semantic relations defined in WordNet (e.g., hypernymy and meronymy) and further populate the relation set by connecting a synset to all the other synsets that appear in its disambiguated gloss.
Resource Alignment
For instance, WordNet can be readily represented as an undirected graph G whose nodes are synsets and edges are modeled after the relations between synsets defined in WordNet (e. g., hypernymy, meronymy, etc.
Resource Alignment
), and LG is the mapping between each synset node and the set of synonyms which express the concept.
Resource Alignment
3'For instance, we calculated that more than 80% of the words in WordNet are monosemous, with over 60% of all the synsets containing at least one of them.
synsets is mentioned in 5 sentences in this paper.
Topics mentioned in this paper:
Tsvetkov, Yulia and Boytsov, Leonid and Gershman, Anatole and Nyberg, Eric and Dyer, Chris
Model and Feature Extraction
A lexical item can belong to several synsets , which are associated with different supersenses.
Model and Feature Extraction
For example, the word head (when used as a noun) participates in 33 synsets , three of which are related to the supersense noan.b0dy.
Model and Feature Extraction
Hence, we select all the synsets of the nouns head and brain.
synsets is mentioned in 5 sentences in this paper.
Topics mentioned in this paper:
Vannella, Daniele and Jurgens, David and Scarfini, Daniele and Toscani, Domenico and Navigli, Roberto
Experiments
A task begins with a description of a target synset and its textual definition; following, ten annotation questions are shown.
Video Game with a Purpose Design
First, by connecting WordNet synsets to Wikipedia pages, most synsets are associated with a set of pictures; while often noisy, these pictures sometimes illustrate the target concept and are an ideal case for validation.
Video Game with a Purpose Design
Data We created a common set of concepts, 0, used in both games, containing sixty synsets selected from all BabelNet synsets with at least fifty associated images.
Video Game with a Purpose Design
Using the same set of synsets , separate datasets were created for the two validation tasks.
synsets is mentioned in 5 sentences in this paper.
Topics mentioned in this paper:
Bansal, Mohit and Burkett, David and de Melo, Gerard and Klein, Dan
Experiments
To project WordNet synsets to terms, we used the first (most frequent) term in each synset .
Experiments
A few WordNet synsets have multiple parents so we only keep the first of each such pair of overlapping trees.
Experiments
We also discard a few trees with duplicate terms because this is mostly due to the projection of different synsets to the same term, and theoretically makes the tree a graph.
synsets is mentioned in 3 sentences in this paper.
Topics mentioned in this paper:
Bengoetxea, Kepa and Agirre, Eneko and Nivre, Joakim and Zhang, Yue and Gojenola, Koldo
Experimental Framework
WordNet is organized into sets of synonyms, called synsets (SS).
Experimental Framework
Each synset in turn belongs to a unique semantic file (SF).
Experimental Framework
As an example, knife in its tool sense is in the EDGE TOOL USED AS A CUTTING INSTRUMENT singleton synset , and also in the ARTIFACT SF along with thousands of words including cutter.
synsets is mentioned in 3 sentences in this paper.
Topics mentioned in this paper:
Flati, Tiziano and Vannella, Daniele and Pasini, Tommaso and Navigli, Roberto
Comparative Evaluation
As regards recall, we note that in two cases (i.e., DBpedia returning page super-types from its upper taxonomy, YAGO linking categories to WordNet synsets) the generalizations are neither pages nor categories and that MENTA returns heterogeneous hypernyms as mixed sets of WordNet synsets , Wikipedia pages and categories.
Comparative Evaluation
MENTA seems to be the closest resource to ours, however, we remark that the hypernyms output by MENTA are very heterogeneous: 48% of answers are represented by a WordNet synset , 37% by Wikipedia categories and 15% are Wikipedia pages.
Introduction
However, unlike the case with smaller manually-curated resources such as WordNet (Fellbaum, 1998), in many large automatically-created resources the taxonomical information is either missing, mixed across resources, e.g., linking Wikipedia categories to WordNet synsets as in YAGO, or coarse-grained, as in DBpedia whose hypernyms link to a small upper taxonomy.
synsets is mentioned in 3 sentences in this paper.
Topics mentioned in this paper:
Litkowski, Ken
Assessment of Lexical Resources
This includes the WordNet lexicographer’s file name (e.g., noun.time), synsets , and hypernyms.
Assessment of Lexical Resources
We make extensive use of the file name, but less so from the synsets and hypernyms.
Assessment of Lexical Resources
However, in general, we find that the file names are too coarse-grained and the synsets and hypernyms too fine-grained for generalizations on the selectors for the complements and the governors.
synsets is mentioned in 3 sentences in this paper.
Topics mentioned in this paper: