Search Results for author: John Philip McCrae

Found 25 papers, 3 papers with code

A Dataset for Term Extraction in Hindi

no code implementations TERM (LREC) 2022 Shubhanker Banerjee, Bharathi Raja Chakravarthi, John Philip McCrae

Automatic Term Extraction (ATE) is one of the core problems in natural language processing and forms a key component of text mining pipelines of domain specific corpora.

Machine Translation Term Extraction

Adaptation of Word-Level Benchmark Datasets for Relation-Level Metaphor Identification

no code implementations WS 2020 Omnia Zayed, John Philip McCrae, Paul Buitelaar

The majority of current approaches pertaining to metaphor processing concentrate on word-level processing due to data availability.

Relation

Recent Developments for the Linguistic Linked Open Data Infrastructure

no code implementations LREC 2020 Thierry Declerck, John Philip McCrae, Matthias Hartung, Jorge Gracia, Christian Chiarcos, Elena Montiel-Ponsoda, Philipp Cimiano, Artem Revenko, Roser Saur{\'\i}, Deirdre Lee, Stefania Racioppa, Jamal Abdul Nasir, Matthias Orlikowsk, Marta Lanau-Coronas, Christian F{\"a}th, Mariano Rico, Mohammad Fazleh Elahi, Maria Khvalchik, Meritxell Gonzalez, Katharine Cooney

In this paper we describe the contributions made by the European H2020 project {``}Pr{\^e}t-{\`a}-LLOD{''} ({`}Ready-to-use Multilingual Linked Language Data for Knowledge Services across Sectors{'}) to the further development of the Linguistic Linked Open Data (LLOD) infrastructure.

Modelling Frequency and Attestations for OntoLex-Lemon

no code implementations LREC 2020 Christian Chiarcos, Maxim Ionov, Jesse de Does, Katrien Depuydt, Anas Fahad Khan, S Stolk, er, Thierry Declerck, John Philip McCrae

Therefore, the OntoLex community has put forward the proposal for a novel module for frequency, attestation and corpus information (FrAC), that not only covers the requirements of digital lexicography, but also accommodates essential data structures for lexical information in natural language processing.

Challenges of Word Sense Alignment: Portuguese Language Resources

no code implementations LREC 2020 Ana Salgado, Sina Ahmadi, Alberto Sim{\~o}es, John Philip McCrae, Rute Costa

Word sense alignment involves searching for matching senses within dictionary entries of different lexical resources and linking them, which poses significant challenges.

Some Issues with Building a Multilingual Wordnet

no code implementations LREC 2020 Francis Bond, Luis Morgado da Costa, Michael Wayne Goodman, John Philip McCrae, Ahti Lohk

In this paper we discuss the experience of bringing together over 40 different wordnets.

Figure Me Out: A Gold Standard Dataset for Metaphor Interpretation

no code implementations LREC 2020 Omnia Zayed, John Philip McCrae, Paul Buitelaar

Metaphor comprehension and understanding is a complex cognitive task that requires interpreting metaphors by grasping the interaction between the meaning of their target and source concepts.

Retrieval Semantic Similarity +2

On the Linguistic Linked Open Data Infrastructure

no code implementations LREC 2020 Christian Chiarcos, Bettina Klimek, Christian F{\"a}th, Thierry Declerck, John Philip McCrae

In this paper we describe the current state of development of the Linguistic Linked Open Data (LLOD) infrastructure, an LOD(sub-)cloud of linguistic resources, which covers various linguistic data bases, lexicons, corpora, terminology and metadata repositories. We give in some details an overview of the contributions made by the European H2020 projects {``}Pr{\^e}t-{\`a}-LLOD{''} ({`}Ready-to-useMultilingual Linked Language Data for Knowledge Services across Sectors{'}) and {``}ELEXIS{''} ({`}European Lexicographic Infrastructure{'}) to the further development of the LLOD.

English WordNet 2020: Improving and Extending a WordNet for English using an Open-Source Methodology

no code implementations LREC 2020 John Philip McCrae, Alex Rademaker, re, Ewa Rudnicka, Francis Bond

WordNet, while one of the most widely used resources for NLP, has not been updated for a long time, and as such a new project English WordNet has arisen to continue the development of the model under an open-source paradigm.

Identification of Adjective-Noun Neologisms using Pretrained Language Models

1 code implementation WS 2019 John Philip McCrae

Neologism detection is a key task in the constructing of lexical resources and has wider implications for NLP, however the identification of multiword neologisms has received little attention.

Word Embeddings

Phrase-Level Metaphor Identification Using Distributed Representations of Word Meaning

no code implementations WS 2018 Omnia Zayed, John Philip McCrae, Paul Buitelaar

Metaphor is an essential element of human cognition which is often used to express ideas and emotions that might be difficult to express using literal language.

Machine Translation Semantic Textual Similarity +3

Expanding wordnets to new languages with multilingual sense disambiguation

no code implementations COLING 2016 Mihael Arcan, John Philip McCrae, Paul Buitelaar

The translation of wordnets is fundamentally complex because of the need to translate all senses of a word including low frequency senses, which is very challenging for current machine translation approaches.

Information Retrieval Machine Translation +3

The Open Linguistics Working Group: Developing the Linguistic Linked Open Data Cloud

no code implementations LREC 2016 John Philip McCrae, Christian Chiarcos, Francis Bond, Philipp Cimiano, Thierry Declerck, Gerard de Melo, Jorge Gracia, Sebastian Hellmann, Bettina Klimek, Steven Moran, Petya Osenova, Antonio Pareja-Lora, Jonathan Pool

The Open Linguistics Working Group (OWLG) brings together researchers from various fields of linguistics, natural language processing, and information technology to present and discuss principles, case studies, and best practices for representing, publishing and linking linguistic data collections.

Cannot find the paper you are looking for? You can Submit a new open access paper.