• Publications
  • Influence
SemEval-2007 Task 19: Frame Semantic Structure Extraction
TLDR
This task consists of recognizing words and phrases that evoke semantic frames as defined in the FrameNet project, and their semantic dependents, which are usually, but not always, their syntactic dependents (including subjects). Expand
  • 125
  • 30
  • PDF
The SALSA Corpus: a German Corpus Resource for Lexical Semantics
TLDR
This paper describes the SALSA corpus, a large German corpus manually annotated with role-semantic information, based on the syntactically annotated TIGER newspaper corpus. Expand
  • 207
  • 29
  • PDF
A Structured Vector Space Model for Word Meaning in Context
TLDR
We address the task of computing vector space representations for the meaning of word occurrences, which can vary widely according to context. Expand
  • 370
  • 23
  • PDF
Inclusive yet Selective: Supervised Distributional Hypernymy Detection
TLDR
We test the Distributional Inclusion Hypothesis, which states that hypernyms tend to occur in a superset of contexts in which their hyponyms are found. Expand
  • 155
  • 18
  • PDF
A Simple, Similarity-based Model for Selectional Preferences
TLDR
We propose a new, simple model for the automatic induction of selectional preferences, using corpus-based semantic similarity metrics. Expand
  • 156
  • 16
  • PDF
Investigations on Word Senses and Word Usages
TLDR
The vast majority of work on word sense tagging has relied on predefined sense inventories and an annotation schema where each word instance is tagged with the best fitting sense. Expand
  • 77
  • 15
  • PDF
A Flexible, Corpus-Driven Model of Regular and Inverse Selectional Preferences
TLDR
We present a vector space–based model for selectional preferences that predicts plausibility scores for argument headwords. Expand
  • 101
  • 10
  • PDF
Towards a Resource for Lexical Semantics: A Large German Corpus with Extensive Semantic Annotation
TLDR
We describe the ongoing construction of a large, semantically annotated corpus resource as reliable basis for the large-scale acquisition of word-semantic information, e.g. the construction of domain-independent lexica. Expand
  • 103
  • 10
  • PDF
What Substitutes Tell Us - Analysis of an "All-Words" Lexical Substitution Corpus
TLDR
We present the first large-scale English “allwords lexical substitution” corpus, comparing them to WordNet synsets. Expand
  • 61
  • 10
  • PDF
...
1
2
3
4
5
...