Summary of the paper
| Title | Turk Bootstrap Word Sense Inventory 2.0: A Large-Scale Resource for Lexical Substitution |
|---|---|
| Authors | Chris Biemann |
| Abstract | This paper presents the Turk Bootstrap Word Sense Inventory (TWSI) 2.0. This lexical resource, created by a crowdsourcing process using Amazon Mechanical Turk (http://www.mturk.com), encompasses a sense inventory for lexical substitution for 1,012 highly frequent English common nouns. Along with each sense, a large number of sense-annotated occurrences in context are given, as well as a weighted list of substitutions. Sense distinctions are not motivated by lexicographic considerations, but driven by substitutability: two usages belong to the same sense if their substitutions overlap considerably. After laying out the need for such a resource, the data is characterized in terms of organization and quantity. Then, we briefly describe how this data was used to create a system for lexical substitutions. Training a supervised lexical substitution system on a smaller version of the resource resulted in well over 90% acceptability for lexical substitutions provided by the system. Thus, this resource can be used to set up reliable, enabling technologies for semantic natural language processing (NLP), some of which we discuss briefly. |
| Topics | Lexicon, lexical database, Semantics, Word Sense Disambiguation |
Full paper  |
Turk Bootstrap Word Sense Inventory 2.0: A Large-Scale Resource for Lexical Substitution |
| Bibtex | @InProceedings{BIEMANN12.252, author = {Chris Biemann}, title = {Turk Bootstrap Word Sense Inventory 2.0: A Large-Scale Resource for Lexical Substitution}, booktitle = {Proceedings of the Eight International Conference on Language Resources and Evaluation (LREC'12)}, year = {2012}, month = {may}, date = {23-25}, address = {Istanbul, Turkey}, editor = {Nicoletta Calzolari (Conference Chair) and Khalid Choukri and Thierry Declerck and Mehmet Uğur Doğan and Bente Maegaard and Joseph Mariani and Asuncion Moreno and Jan Odijk and Stelios Piperidis}, publisher = {European Language Resources Association (ELRA)}, isbn = {978-2-9517408-7-7}, language = {english} } |