Multilingual resources for NLP in the lexical markup framework (LMF)

Francopoulo, Gil; Rafecas, Núria Bel; George, Monte; Calzolari, Nicoletta; Monachini, Monica; Pet, Mandy; Soria, Claudia

doi:10.1007/s10579-008-9077-5

Cited by 32 publications

(16 citation statements)

References 4 publications

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“…For example, the Lexical Markup Framework (LMF; Francopoulo et al, 2009) was especially proposed for modelling MRDs and lexicons for use with NLP applications. While both standards include guidelines for modelling MRDs and lexicons, TEI is more popular in the social sciences, while LMF is more popular among computer scientists and NLP researchers, perhaps due to their different purposes.…”

Section: Standards For Modelling and Marking Up Dictionariesmentioning

confidence: 99%

Digitising a machine-tractable version of Kamus Dewan with TEI-P5

Tze

Chiew

Tang

et al. 2016

Preprint

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Kamus Dewan is the authoritative dictionary for Bahasa Malaysia, containing a wealth of linguistic and cultural information about Bahasa Malaysia. It is currently available in print, as well as an searchable online dictionary. However, the online dictionary lacks advanced search capabilities that target specific fields within each headword and lemma entry. For these information to be targeted and extracted efficiently by computers, the macro-and micro-structures of Kamus Dewan entries need to be first annotated or marked up explicitly. We describe how TEI-P5 guidelines have been applied in this endeavour to make the Kamus Dewan more machine-tractable. We also give some examples of how the machine-tractable data from Kamus Dewan can be used for linguistic research and analysis, as well as for producing other language resources.

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Section: Standards For Modelling and Marking Up Dictionariesmentioning

confidence: 99%

Digitising a machine-tractable version of Kamus Dewan with TEI-P5

Tze

Chiew

Tang

et al. 2016

Preprint

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“…This is the simplest macrostructure for a pivot-based multilingual lexical resource that allows for the extraction of usage dictionaries for all pairs in all directions. The concept of axie-based pivot structure has been validated by the Papillon project and then included in the Lexical Markup Framework standard (Francopoulo et al 2009). …”

Section: Lexical Databasesmentioning

confidence: 99%

Proceedings of the 4th Workshop on Cognitive Aspects of the Lexicon (CogALex)

Zock¹,

Rapp²,

Huang³

2014

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“…The elements that are part of this output are mainly NEs, orthographic variants of these NEs and classes to which these NEs belong (by means of "instance of" relations). Due to the fact that this data could be naturally represented by means of a LR and because we build with it a LR we have decided to follow the Lexicon Markup Framework (LMF), an ISO standard for the representation of lexicons (Francopoulo et al, 2008) (ISO 24613, 2008), in order to encode the output.…”

Section: The Named Entity Lexiconmentioning

confidence: 99%

Web 2.0, Language Resources and standards to automatically build a multilingual Named Entity Lexicon

Toral

Ferrández

Monachini

et al. 2011

Lang Resources & Evaluation

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This paper proposes to advance in the current state-of-the-art of automatic Language Resource (LR) building by taking into consideration three elements: (i) the knowledge available in existing LRs, (ii) the vast amount of information available from the collaborative paradigm that has emerged from the Web 2.0 and (iii) the use of standards to improve interoperability.We present a case study in which a set of LRs for different languages (WordNet for English and Spanish and Parole-Simple-Clips for Italian) are extended with Named Entities (NE) by exploiting Wikipedia and the aforementioned LRs. The practical result is a multilingual NE lexicon connected to these LRs and to two ontologies: SUMO and SIMPLE. Furthermore, the paper addresses an important problem which affects the Computational Linguistics area in the present, interoperability, by making use of the ISO LMF standard to encode this lexicon. The different steps of the procedure (mapping, disambiguation, extraction, NE identification and postprocessing) are comprehensively explained and evaluated. The resulting resource contains 974,567, 137,583 and 125,806 NEs for English, Spanish and Italian respectively. Finally, in order to check the usefulness of the constructed resource, we apply it into a state-of-the-art Question Answering system and evaluate its impact; the NE lexicon improves the system's accuracy by 28.1%. Compared to previous approaches to build NE repositories, the current proposal represents a step forward in terms of automation, language independence, amount of NEs acquired and richness of the information represented.

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Multilingual resources for NLP in the lexical markup framework (LMF)

Cited by 32 publications

References 4 publications

Digitising a machine-tractable version of Kamus Dewan with TEI-P5

Digitising a machine-tractable version of Kamus Dewan with TEI-P5

Proceedings of the 4th Workshop on Cognitive Aspects of the Lexicon (CogALex)

Web 2.0, Language Resources and standards to automatically build a multilingual Named Entity Lexicon

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