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Text to Terminological Concept System Text2TCS

Domaine:

natural language processing

Type de record:

software
Créateur:
Gro
Éditeur:
ELGELGGro
Éditeur:
University of Vienna
Hôte:avatar
Text2TCS automatically extracts terminological concept systems from natural language text. Terms are domain-specific natural language expressions that describe domain-specific concepts. It extracts terms, concepts and concept relations and represent them in a terminological concept system, building on a prespecified relation typology: generic, partitive, activity, associative, causal, spatial, instrumental, origination, and property relations. Syonyms are detected and finally grouped in the output format (text and TBX/XML).

The system has been trained on English and German but builds on a pre-trained multilingual neural model (XLM-R) that allows Text2TCS to transfer its functionality to the following languages: Afrikaans, Albanian, Amharic, Arabic, Armenian, Assamese, Azerbaijani, Basque, Belarusian, Bengali, Bengali Romanized, Bosnian, Breton, Bulgarian, Burmese, Catalan, Chinese (Simplified), Chinese (Traditional), Croatian, Czech, Danish, Dutch, English, Esperanto, Estonian, Filipino, Finnish, French, Galician, Georgian, German, Greek, Gujarati, Hausa, Hebrew, Hindi, Hindi Romanized, Hungarian, Icelandic, Indonesian, Irish, Italian, Japanese, Javanese, Kannada, Kazakh, Khmer, Korean, Kurdish (Kurmanji), Kyrgyz, Lao, Latin, Latvian, Lithuanian, Macedonian, Malagasy, Malay, Malayalam, Marathi, Mongolian, Nepali, Norwegian, Oriya, Oromo, Pashto, Persian, Polish, Portuguese, Punjabi, Romanian, Russian, Sanskri, Scottish, Gaelic, Serbian, Sindhi, Sinhala, Slovak, Slovenian, Somali, Spanish, Sundanese, Swahili, Swedish, Tamil, Tamil Romanized, Telugu, Telugu Romanized, Thai, Turkish, Ukrainian, Urdu, Urdu Romanized, Uyghur, Uzbek, Vietnamese, Welsh, Western, Frisian, Xhosa, Yiddish.

The list of input and output languages below is more restrictive since we utilize an automated language recognition tool and a sentence tokenizer. The indicated languages represent the languages officially supported by those two tools and XLM-R, even though our application might be able to also process other languages from the list above.