and the Role of a Generative Lexicon. Sabine Bergler. 6.1 Introduction. Recent advances in language technologies in areas such as information extraction. ( MUC1), question answering (TREC2), and summarization (DUC3) have explored extensively the power of statistical NLP in the age of ready availability of large, an -.

Chapter 3. A Type Composition Logic for Generative. Lexicon. Nicholas Asher and James Pustejovsky. 3.1 Introduction1. Recent work in discourse semantics has focused on modeling the ... (eds.), Advances in Generative Lexicon Theory, Text,. Speech and Language Technology 46, DOI 10.1007/978-94-007-5189-7 3, .

Computational lexicons can play a key role in the Semantic Web: aiming at making word content machine-understandable, they intend to provide an explicit representa- tion of word meaning, so that it can be directly accessed and used by computational agents, such as large-coverage parsers, modules for intelligent ...

A fundamental issue dividing theories of the syntax-semantics interface is whether the semantic representation of clauses is projected from the lexical representation of the verb which determines to a large extent the syntactic structure of the clause or whether it is constructed or composed based on the NPs and PPs ...

argument selection in Pustejovsky (2011). J. Pustejovsky ( ). Department of Computer Science, Brandeis University, Waltham, MA, USA e-mail: [email protected] brandeis.edu. J. Pustejovsky et al. (eds.), Advances in Generative Lexicon Theory, Text,. Speech and Language Technology 46, DOI 10.1007/978-94-007- 5189-7 2,.

... Language Education, Silla University, Busan, South Korea. C. Lee ( ). Department of Linguistics, Seoul National University, Seoul, South Korea e-mail: [email protected] J. Pustejovsky et al. (eds.), Advances in Generative Lexicon Theory, Text,. Speech and Language Technology 46, DOI 10.1007/978-94-007- 5189-7 10,.

Generative Lexicon Theory and Linguistic Linked Open Data. Fahad Khan. Francesca ... Language (OWL)2 a family of formal knowledge representation languages of varying degrees of ex- pressivity developed for the purpose of building ontologies. For the Language Resources and Technology. (LRT) community the ...

3. Apr. 2013 ... 2013.10. Advances in generative lexicon theory. / Hrsg.: James Pustejovsky, Pierrette Bouillon, Hitoshi Isahara, Kyoko Kanzaki, Chungmin. Lee. -. Dordrecht [ u.a.]: Springer, 2013. - VIII, 488 S. : graph. Darst. (Text, speech and language technology; 46). ISBN 978-94-007-5188-0. Per 106-051. Verbeke ...

machine-readable text made possible by advances in computer technology. According to John Sinclair, a ... corpus in order to obtain “genuine instances of language in use” (Sinclair, 1991: 4–5). All this was thought to ..... Regular alternations as described by Pustejovsky in his Generative Lexicon Theory. (see Pustejovsky ...

Deep Learning for Speech/Language. Processing. --- machine learning & signal processing perspectives. Li Deng. Deep Learning Technology Center. Microsoft Research, Redmond, USA. Tutorial given at Interspeech, Sept 6, 2015. Thanks go to many colleagues at DLTC/MSR, collaborating universities, and at Microsoft's ...

May 4, 2017 ... 2007: Associate Professor at the 2nd Internationsl PhD School in Language and Speech Technologies, 2006-. 2008, Rovira i Virgili University, Tarragona, .... invited seminars, tutorials and panels. 1996: Invited lecture at the Workshop " From Lexicon to Text: The Computational and Theoretical Issues in.

text. Part of speech tagging it describes a sentence, determines the part of speech for each word. Though NLP tasks are obviously very closely interweaved but ... of human language. The field of Natural Language Processing is related with different theories and techniques that deal with the problem of natural language of ...

Speech and Language Technologies, Apple Technologies Inc., Cupertino, CA 95014, USA. Abstract. Pustejovsky, J. and B. .... texts facilitate systematic incorporation of world knowledge into the lexicon. On the other hand, these ... The generative theory of lexical semantics imposes a strong focus on cur- rent efforts to derive ...

Natural Language Processing Using Very. Large Corpora. Susan Armstrong, Kenneth Church, Pierre ... (Text, speech and language technology series, edited by Nancy Ide and Jean. Véronis, volume 11), 1999, ... rules for part-of-speech tagging” by Eric. Brill and Mihai Pop. “Tagging French without lexical probabilities .

it on real text. Our focus has been on proving the feasibility of our design. 1. Introduction. 1.1 Gaps. One of the central facts about language is that speakers regularly .... We are working from a corpus of written texts, not speech. ..... Lexical entries in the generative lexicon In Pustejovsky's Generative Lexicon theory ( Puste-.

(CSC2523, 'Visual Recognition with Text', UToronto, Winter 2015 – 01/21/2015). ( various slides .... Collins, 1999 → 88.6 F1 (generative lexical). Charniak and Johnson ...... Language Technologies: The 2010 Annual Conference of the North American Chapter of the Association for Computational Linguistics. Association for ...

Part of the Text, Speech and Language Technology book series (TLTB, volume 33) ... We argue that the level of sense-discrimination that natural language processing (NLP) needs corresponds roughly to homographs, though we discuss psycholinguistic evidence that there are broad sense divisions with some etymological ...

In this section, we examine different theories concerning this topic, especially the model proposed by Pustejovsky. (1995). We then discuss the case of NEs and examine previous work dealing with related questions using Natural. Language Processing techniques. Pustejovsky's Generative lexicon (1995). Pustejovsky ...

Abstract. This study explores how second language (L2) texts written by learners at various proficiency levels can be classified using computational indices that characterize lexical competence. For this study, 100 writing samples taken from 100 L2 learners were analyzed using lexical indices reported by the computational ...

Jun 23, 2011 ... is only to be expected that speech recognition advances make spoken language as .... Complete test set. 168. 1344. 0.81. Table 1. TIMIT Corpus training and test sets. TIMIT original transcriptions are based on 61 phones, presented in .... The major advantage of generative learning is that it is relatively.