acl 2016 论文列表Proceedings of the Fifth Joint Conference on Lexical and Computational Semantics, *SEM@ACL 2016, Berlin, Germany, 11-12 August 2016. |
Learning Embeddings to lexicalise RDF Properties.
Approximating Givenness in Content Assessment through Distributional Semantics.
A Compositional-Distributional Semantic Model for Searching Complex Entity Categories.
Random Positive-Only Projections: PPMI-Enabled Incremental Semantic Space Construction.
You and me... in a vector space: modelling individual speakers with distributional semantics.
A Study of Suggestions in Opinionated Texts and their Automatic Detection.
Detecting Stance in Tweets And Analyzing its Interaction with Sentiment.
The Role of Modifier and Head Properties in Predicting the Compositionality of English and German Noun-Noun Compounds: A Vector-Space Perspective.
Orthogonality regularizer for question answering.
Taking the best from the Crowd: Learning Question Passage Classification from Noisy Data.
Improving Text-to-Pictograph Translation Through Word Sense Disambiguation.
Unsupervised Text Segmentation Using Semantic Relatedness Graphs.
Linguistic Style Accommodation in Disagreements.
So-Called Non-Subsective Adjectives.
Adding Context to Semantic Data-Driven Paraphrasing.
Leveraging VerbNet to build Corpus-Specific Verb Clusters.
When Hyperparameters Help: Beneficial Parameter Combinations in Distributional Semantic Models.
Improving Zero-Shot-Learning for German Particle Verbs by using Training-Space Restrictions and Local Scaling.
Sense Embedding Learning for Word Sense Induction.
How Factuality Determines Sentiment Inferences.
Natural Solution to FraCaS Entailment Problems.
Driving inversion transduction grammar induction with semantic evaluation.
Implicit Semantic Roles in a Multilingual Setting.
High-Fidelity Lexical Axiom Construction from Verb Glosses.
Metaphor as a Medium for Emotion: An Empirical Study.
Automatic Identification of Aspectual Classes across Verbal Readings.
Quantificational features in distributional word representations.