[PDF] Top 20 Semantic Frame Identification with Distributed Word Representations
Has 10000 "Semantic Frame Identification with Distributed Word Representations" found on our website. Below are the top 20 most common "Semantic Frame Identification with Distributed Word Representations".
Semantic Frame Identification with Distributed Word Representations
... features: word, the word clus- ter, word suffixes of length 1, 2 and 3, capitaliza- tion, whether it has a hyphen, digit and punctua- ...same word clusters for the argu- ment ... See full document
11
Do Distributed Semantic Models Dream of Electric Sheep? Visualizing Word Representations through Image Synthesis
... 3 Experiment 1: Naming the dream Task definition and data collection In this ex- periment we presented a dream, and asked sub- jects if they thought it was more likely to denote the correct dreamed word or a ... See full document
6
Composition of Word Representations Improves Semantic Role Labelling
... and word spans, which serve as supplementary features for classifi- ...for word representation has been a motivation for de- veloping representations of larger constructions such as phrases and ... See full document
7
Learning Hidden Markov Models with Distributed State Representations for Domain Adaptation
... a semantic word by a single discrete state value is too re- strictive, as it has been shown in the literature that words have many different features in a multi- dimensional space where they could be ... See full document
6
Proceedings of the IWCS Workshop Vector Semantics for Discourse and Dialogue
... In this talk, I will address the question of whether it makes sense to represent a sentence as a single point in space or whether it is better represented as a collection of contextualised points. The answer is of course ... See full document
5
Cross Lingual Syntactically Informed Distributed Word Representations
... cross-lingual word em- bedding model which injects syntactic information into a cross-lingual word vector space, resulting in improved modeling of functional similarity, as evidenced by improvements on ... See full document
7
L2F/INESC ID at SemEval 2019 Task 2: Unsupervised Lexical Semantic Frame Induction using Contextualized Word Representations
... on semantic role ...duces semantic roles for each predicate indepen- dently using an iterative clustering approach, start- ing with one cluster per ... See full document
7
Learning Cross lingual Distributed Logical Representations for Semantic Parsing
... in semantic parsing comes with instances consisting of logical forms annotated with sentences from multiple different ...monolingual semantic parser for each language, while leveraging useful information ... See full document
7
Syntactic Dependencies and Distributed Word Representations for Analogy Detection and Mining
... It has also been shown in Section 6.3 that the performances of analogy detection vary across dif- ferent types of relations, which indicates that there are more sophisticated underlying factors. One in- tuitive ... See full document
10
Is “Universal Syntax” Universally Useful for Learning Distributed Word Representations?
... Evaluation Our cross-linguistic study is made possible not only thanks to the “universal NLP” initiative but also owing to the benchmarking eval- uation sets for other languages beyond English (i.e., IT, DE) that have ... See full document
7
Evaluating distributed word representations for capturing semantics of biomedical concepts
... the word in- dex is 1 while the other elements are ...and distributed representa- ...Distributional representations are mainly based on co-occurrence matrix O of words in the vocabulary and their ... See full document
6
Toward a cognitive dependency grammar of Hungarian
... Three semantic dimensions have been introduced for frame semantic relations (S1), speech function (S2) and contextualization (S3), linked to one or more of the formal representations F1 ... See full document
8
Distributed Word Representations Improve NER for e Commerce
... and semantic properties of the tokens. While discrete word rep- resentations derived from word clusters have been shown to be very beneficial to NER (Miller et ...to distributed word ... See full document
8
Polyglot: Distributed Word Representations for Multilingual NLP
... plications. Word clustering has been used to learn classes of words that have similar semantic fea- tures to improve language modeling (Brown et ...induce distributed representations for a ... See full document
10
Unsupervised Topic Modeling for Short Texts Using Distributed Representations of Words
... tributed representations of words over sufficiently long context windows and subsequently use Gaus- sian mixture models to parameterize the vector space represented by the distributed representa- ... See full document
9
Unsupervised Induction of Frame Semantic Representations
... for word-sense induction hardly beat most- frequent-sense baselines in accuracy metrics (Man- andhar et ...pervised semantic parsing tasks (Poon and Domin- gos, 2009; Poon and Domingos, 2010; Titov and ... See full document
7
Phrase Level Metaphor Identification Using Distributed Representations of Word Meaning
... The semantic similarities between the word embeddings vectors of the seed and the two candidates measured by the cosine similarity func- tion are ...2013) word embedding model on the Google News ... See full document
10
Distributed Representations for Unsupervised Semantic Role Labeling
... In contrast to previous word-based approaches, our model induces vector representations for each predicate and its semantic arguments. As a learn- ing objective, vectors are required to contribute to ... See full document
10
The Role of Protected Class Word Lists in Bias Identification of Contextualized Word Representations
... Contextualized word representations are replac- ing word vectors in many natural language pro- cessing (NLP) tasks such as sentiment analysis, coreference resolution, question answering, tex- tual ... See full document
7
What a neural language model tells us about spatial relations
... what semantic knowledge about spatial relations is captured in representations of a generative neural language ...the word embeddings which are a form of internal semantic ... See full document
11
Related subjects